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ORCIDBalaraman Ravindran
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- affiliation: Indian Institute of Technology Madras
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2020 – today
- 2024
[j29]Sudarsun Santhiappan
, Jeshuren Chelladurai, Balaraman Ravindran:
TOMBoost: a topic modeling based boosting approach for learning with class imbalance. Int. J. Data Sci. Anal. 17(4): 389-409 (2024)- [c152]Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran:
MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning. AAMAS 2024: 1865-1873 - [c151]Richa Verma, Durgesh Kalwar, Harshad Khadilkar, Balaraman Ravindran:
Guiding Offline Reinforcement Learning Using a Safety Expert. COMAD/CODS 2024: 82-90 - [c150]Siddharth Nishtala, Balaraman Ravindran:
Cost-Sensitive Trees for Interpretable Reinforcement Learning. COMAD/CODS 2024: 91-99 - [c149]Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan, Hardik Meisheri, Harshad Khadilkar, Balaraman Ravindran:
A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce. COMAD/CODS 2024: 430-438 - [c148]Sangameshwar Patil, Balaraman Ravindran:
Zero-shot Learning based Alternatives for Class Imbalanced Learning Problem in Enterprise Software Defect Analysis. MSR 2024: 140-141 - [i94]Yogesh Tripathi, Raghav Donakanti, Sahil Girhepuje, Ishan Kavathekar, Bhaskara Hanuma Vedula, Gokul S. Krishnan, Shreya Goyal, Anmol Goel, Balaraman Ravindran, Ponnurangam Kumaraguru:
InSaAF: Incorporating Safety through Accuracy and Fairness | Are LLMs ready for the Indian Legal Domain? CoRR abs/2402.10567 (2024) - [i93]Atharvan Dogra, Ameet Deshpande, John Nay, Tanmay Rajpurohit, Ashwin Kalyan, Balaraman Ravindran:
Deception in Reinforced Autonomous Agents: The Unconventional Rabbit Hat Trick in Legislation. CoRR abs/2405.04325 (2024) - [i92]Ambreesh Parthasarathy, Aditya Phalnikar, Ameen Jauhar, Dhruv Somayajula, Gokul S. Krishnan, Balaraman Ravindran:
Participatory Approaches in AI Development and Governance: A Principled Approach. CoRR abs/2407.13100 (2024) - [i91]Ambreesh Parthasarathy, Aditya Phalnikar, Gokul S. Krishnan, Ameen Jauhar, Balaraman Ravindran:
Participatory Approaches in AI Development and Governance: Case Studies. CoRR abs/2407.13103 (2024) - 2023
- [j28]Shreya Goyal, Sumanth Doddapaneni, Mitesh M. Khapra, Balaraman Ravindran:
A Survey of Adversarial Defenses and Robustness in NLP. ACM Comput. Surv. 55(14s): 332:1-332:39 (2023) - [j27]Harsha Kokel, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli:
RePReL: a unified framework for integrating relational planning and reinforcement learning for effective abstraction in discrete and continuous domains. Neural Comput. Appl. 35(23): 16877-16892 (2023) - [j26]Tarun Kumar, Ramanathan Sethuraman, Sanga Mitra, Balaraman Ravindran, Manikandan Narayanan:
MultiCens: Multilayer network centrality measures to uncover molecular mediators of tissue-tissue communication. PLoS Comput. Biol. 19(4) (2023) - [c147]Saket Gurukar, Shaileshh Bojja Venkatakrishnan, Balaraman Ravindran, Srinivasan Parthasarathy:
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks. ASONAM 2023: 245-252 - [c146]Kushal Chauhan, Soumya Chatterjee, Akash Reddy, Aniruddha S, Balaraman Ravindran, Pradeep Shenoy:
Matching Options to Tasks using Option-Indexed Hierarchical Reinforcement Learning. AAMAS 2023: 2631-2633 - [c145]Mayuresh Kunjir, Sanjay Chawla, Siddarth Chandrasekar, Devika Jay, Balaraman Ravindran:
Optimizing Traffic Control with Model-Based Learning: A Pessimistic Approach to Data-Efficient Policy Inference. KDD 2023: 1176-1187 - [c144]Adithya Ramesh, Balaraman Ravindran:
Physics-Informed Model-Based Reinforcement Learning. L4DC 2023: 26-37 - [c143]Naganand Yadati, Tarun Kumar, Deepak Maurya, Balaraman Ravindran, Partha P. Talukdar:
HEAL: Unlocking the Potential of Learning on Hypergraphs Enriched With Attributes and Layers. LoG 2023: 34 - [c142]Tamizharasan Kanagamani, Madhuvanthi Muliya, V. Srinivasa Chakravarthy, Balaraman Ravindran, Ramshekhar N. Menon:
Oscillatory Network and Deep Value Network Based Memory Replay Model of Hippocampus. PReMI 2023: 117-127 - [i90]Sahil Girhepuje, Anmol Goel, Gokul S. Krishnan, Shreya Goyal, Satyendra Pandey, Ponnurangam Kumaraguru, Balaraman Ravindran:
Are Models Trained on Indian Legal Data Fair? CoRR abs/2303.07247 (2023) - [i89]Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran:
Bi-level Latent Variable Model for Sample-Efficient Multi-Agent Reinforcement Learning. CoRR abs/2304.06011 (2023) - [i88]Sudarsun Santhiappan, Nitin Shravan, Balaraman Ravindran:
Clustering Indices based Automatic Classification Model Selection. CoRR abs/2305.13926 (2023) - [i87]Returaj Burnwal, Anirban Santara, Nirav P. Bhatt, Balaraman Ravindran, Gaurav Aggarwal:
GAN-MPC: Training Model Predictive Controllers with Parameterized Cost Functions using Demonstrations from Non-identical Experts. CoRR abs/2305.19111 (2023) - [i86]Saket Gurukar, Shaileshh Bojja Venkatakrishnan, Balaraman Ravindran, Srinivasan Parthasarathy:
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks. CoRR abs/2306.14357 (2023) - [i85]Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan, Harshad Khadilkar, Hardik Meisheri, Balaraman Ravindran:
Multi-Agent Learning of Efficient Fulfilment and Routing Strategies in E-Commerce. CoRR abs/2311.16171 (2023) - [i84]Gokul S. Krishnan, Sarala Padi, Craig S. Greenberg, Balaraman Ravindran, Dinesh Manocha, Ram D. Sriram:
LineConGraphs: Line Conversation Graphs for Effective Emotion Recognition using Graph Neural Networks. CoRR abs/2312.03756 (2023) - 2022
- [j25]Balaraman Ravindran, Sunita Sarawagi, Aditi Jain:
AI and data science centers in top Indian academic institutions. Commun. ACM 65(11): 94-97 (2022) - [j24]Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Srinivasan Parthasarathy, Balaraman Ravindran:
Scaling Graph Propagation Kernels for Predictive Learning. Frontiers Big Data 5: 616617 (2022) - [j23]Joseph H. R. Isaac, Manivannan Muniyandi, Balaraman Ravindran:
Single Shot Corrective CNN for Anatomically Correct 3D Hand Pose Estimation. Frontiers Artif. Intell. 5: 759255 (2022) - [j22]Hardik Meisheri, Nazneen N. Sultana, Mayank Baranwal, Vinita Baniwal, Somjit Nath, Satyam Verma, Balaraman Ravindran, Harshad Khadilkar:
Scalable multi-product inventory control with lead time constraints using reinforcement learning. Neural Comput. Appl. 34(3): 1735-1757 (2022) - [j21]Saket Gurukar, Priyesh Vijayan, Srinivasan Parthasarathy, Balaraman Ravindran, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel:
Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress. Trans. Mach. Learn. Res. 2022 (2022) - [c141]Rishi Saket, Aravindan Raghuveer, Balaraman Ravindran:
On Combining Bags to Better Learn from Label Proportions. AISTATS 2022: 5913-5927 - [c140]Jay Nandy, Rishi Saket, Prateek Jain, Jatin Chauhan, Balaraman Ravindran, Aravindan Raghuveer:
Domain-Agnostic Contrastive Representations for Learning from Label Proportions. CIKM 2022: 1542-1551 - [c139]Pranshu Malviya, Balaraman Ravindran, Sarath Chandar:
TAG: Task-based Accumulated Gradients for Lifelong learning. CoLLAs 2022: 366-389 - [c138]Sai Kiran Narayanaswami, Nandan Sudarsanam, Balaraman Ravindran:
An Active Learning Framework for Efficient Robust Policy Search. COMAD/CODS 2022: 1-9 - [c137]Sapana Chaudhary, Balaraman Ravindran:
Smooth Imitation Learning via Smooth Costs and Smooth Policies. COMAD/CODS 2022: 63-71 - [c136]Sruthikeerthi Nandita, Goutham Zampani, Gokul S. Krishnan, Gitakrishnan Ramadurai, Balaraman Ravindran:
Automated Incident Location Identification for EMS from Ambulance Geospatial Data. COMAD/CODS 2022: 162-168 - [c135]Manoj Bharadhwaj, Gitakrishnan Ramadurai, Balaraman Ravindran:
Detecting Vehicles on the Edge: Knowledge Distillation to Improve Performance in Heterogeneous Road Traffic. CVPR Workshops 2022: 3191-3197 - [c134]Harsha Kokel, Nikhilesh Prabhakar, Balaraman Ravindran, Erik Blasch, Prasad Tadepalli, Sriraam Natarajan:
Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion. FUSION 2022: 1-8 - [c133]Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran:
Revisiting Link Prediction on Heterogeneous Graphs with a Multi-view Perspective. ICDM 2022: 358-367 - [c132]Chandrasekar Subramanian, Balaraman Ravindran:
Causal Contextual Bandits with Targeted Interventions. ICLR 2022 - [c131]Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran:
Evolutionary Approach to Security Games with Signaling. IJCAI 2022: 620-627 - [c130]Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran:
Multi-Variate Time Series Forecasting on Variable Subsets. KDD 2022: 76-86 - [i83]Shreya Goyal, Sumanth Doddapaneni, Mitesh M. Khapra, Balaraman Ravindran:
A Survey in Adversarial Defences and Robustness in NLP. CoRR abs/2203.06414 (2022) - [i82]Adam Zychowski, Jacek Mandziuk, Elizabeth Bondi, Aravind Venugopal, Milind Tambe, Balaraman Ravindran:
Evolutionary Approach to Security Games with Signaling. CoRR abs/2204.14173 (2022) - [i81]Kushal Chauhan, Soumya Chatterjee, Akash Reddy, Balaraman Ravindran, Pradeep Shenoy:
Matching options to tasks using Option-Indexed Hierarchical Reinforcement Learning. CoRR abs/2206.05750 (2022) - [i80]Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran:
Multi-Variate Time Series Forecasting on Variable Subsets. CoRR abs/2206.12626 (2022) - [i79]Jeshuren Chelladurai, Sudarsun Santhiappan, Balaraman Ravindran:
GrabQC: Graph based Query Contextualization for automated ICD coding. CoRR abs/2207.06802 (2022) - [i78]Neeraja Kirtane, Jeshuren Chelladurai, Balaraman Ravindran, Ashish V. Tendulkar:
ReGrAt: Regularization in Graphs using Attention to handle class imbalance. CoRR abs/2211.14770 (2022) - [i77]Adithya Ramesh, Balaraman Ravindran:
Physics-Informed Model-Based Reinforcement Learning. CoRR abs/2212.02179 (2022) - 2021
- [j20]Joseph Hosanna Raj Isaac, Manivannan Muniyandi, Balaraman Ravindran:
Corrective Filter Based on Kinematics of Human Hand for Pose Estimation. Frontiers Virtual Real. 2: 663618 (2021) - [j19]Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, Balaraman Ravindran:
MADRaS : Multi Agent Driving Simulator. J. Artif. Intell. Res. 70: 1517-1555 (2021) - [c129]Daksh Anand, Vaibhav Gupta, Praveen Paruchuri, Balaraman Ravindran:
An Enhanced Advising Model in Teacher-Student Framework using State Categorization. AAAI 2021: 6653-6660 - [c128]Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran:
Relational Boosted Bandits. AAAI 2021: 12123-12130 - [c127]Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran:
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal. ACML 2021: 518-533 - [c126]Rajan Kumar Soni, Karthick Seshadri, Balaraman Ravindran:
Metric Learning for comparison of HMMs using Graph Neural Networks. ACML 2021: 1365-1380 - [c125]Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli:
RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction. ICAPS 2021: 533-541 - [c124]Karthik Visweswariah, Beethika Tripathi, Mitesh M. Khapra, Balaraman Ravindran:
A Joint Training Framework for Open-World Knowledge Graph Embeddings. AKBC 2021 - [c123]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
SEERL: Sample Efficient Ensemble Reinforcement Learning. AAMAS 2021: 1100-1108 - [c122]Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe:
Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. AAMAS 2021: 1353-1361 - [c121]Sudarsun Santhiappan, Balaraman Ravindran:
A semi-supervised approach to growing classification trees. COMAD/CODS 2021: 29-37 - [c120]Vaishnavi Muralidharan, Nandan Sudarsanam, Balaraman Ravindran:
Inferring customer occupancy status in for-hire vehicles using PU Learning. COMAD/CODS 2021: 290-298 - [c119]Sudarsun Santhiappan, Nitin Shravan, Balaraman Ravindran:
Is it hard to learn a classifier on this dataset? COMAD/CODS 2021: 299-306 - [c118]Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran:
Semi-Supervised Deep Learning for Multiplex Networks. KDD 2021: 1234-1244 - [c117]Jeshuren Chelladurai, Sudarsun Santhiappan, Balaraman Ravindran:
GrabQC: Graph Based Query Contextualization for Automated ICD Coding. PAKDD (1) 2021: 225-237 - [i76]Jahnvi Patel, Devika Jay, Balaraman Ravindran, K. Shanti Swarup:
Neural Fitted Q Iteration based Optimal Bidding Strategy in Real Time Reactive Power Market_1. CoRR abs/2101.02456 (2021) - [i75]Nahas Pareekutty, Francis James, Balaraman Ravindran, Suril Vijaykumar Shah:
qRRT: Quality-Biased Incremental RRT for Optimal Motion Planning in Non-Holonomic Systems. CoRR abs/2101.02635 (2021) - [i74]Deepak Maurya, Balaraman Ravindran:
Hyperedge Prediction using Tensor Eigenvalue Decomposition. CoRR abs/2102.04986 (2021) - [i73]Siddharth Nishtala, Lovish Madaan, Aditya Mate, Harshavardhan Kamarthi, Anirudh Grama, Divy Thakkar, Dhyanesh Narayanan, Suresh Chaudhary, Neha Madhiwalla, Ramesh Padmanabhan, Aparna Hegde, Pradeep Varakantham, Balaraman Ravindran, Milind Tambe:
Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes. CoRR abs/2103.09052 (2021) - [i72]Pranshu Malviya, Balaraman Ravindran, Sarath Chandar:
TAG: Task-based Accumulated Gradients for Lifelong learning. CoRR abs/2105.05155 (2021) - [i71]Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran:
Semi-Supervised Deep Learning for Multiplex Networks. CoRR abs/2110.02038 (2021) - [i70]Amrit Diggavi Seshadri, Balaraman Ravindran:
Multi-Tailed, Multi-Headed, Spatial Dynamic Memory refined Text-to-Image Synthesis. CoRR abs/2110.08143 (2021) - [i69]Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli:
Dynamic probabilistic logic models for effective abstractions in RL. CoRR abs/2110.08318 (2021) - [i68]Sapana Chaudhary, Balaraman Ravindran:
Smooth Imitation Learning via Smooth Costs and Smooth Policies. CoRR abs/2111.02354 (2021) - [i67]Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran:
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal. CoRR abs/2111.14348 (2021) - 2020
- [j18]Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran:
Hypergraph clustering by iteratively reweighted modularity maximization. Appl. Netw. Sci. 5(1): 52 (2020) - [j17]Sangameshwar Patil, Balaraman Ravindran:
Predicting software defect type using concept-based classification. Empir. Softw. Eng. 25(2): 1341-1378 (2020) - [j16]Abhishek Ghose, Balaraman Ravindran:
Interpretability With Accurate Small Models. Frontiers Artif. Intell. 3: 3 (2020) - [j15]Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran:
Rate of change analysis for interestingness measures. Knowl. Inf. Syst. 62(1): 239-258 (2020) - [j14]Sanjay Ganapathy, Swagath Venkataramani, Giridhur Sriraman, Balaraman Ravindran, Anand Raghunathan:
DyVEDeep: Dynamic Variable Effort Deep Neural Networks. ACM Trans. Embed. Comput. Syst. 19(3): 16:1-16:24 (2020) - [c116]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract). AAAI 2020: 13905-13906 - [c115]Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Towards Transparent and Explainable Attention Models. ACL 2020: 4206-4216 - [c114]Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe:
Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. AAMAS 2020: 575-583 - [c113]Anirban Santara, Rishabh Madan, Pabitra Mitra, Balaraman Ravindran:
ExTra: Transfer-guided Exploration. AAMAS 2020: 1987-1989 - [c112]Siddharth Nayak, Balaraman Ravindran:
Reinforcement Learning for Improving Object Detection. ECCV Workshops (5) 2020: 149-161 - [c111]Sanchari Sen, Balaraman Ravindran, Anand Raghunathan:
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks. ICLR 2020 - [c110]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Understanding Dynamic Scenes using Graph Convolution Networks. IROS 2020: 8279-8286 - [c109]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks. IV 2020: 321-327 - [c108]Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran:
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning. ECML/PKDD (2) 2020: 509-524 - [c107]Anasua Mitra, Priyesh Vijayan, Srinivasan Parthasarathy, Balaraman Ravindran:
A Unified Non-Negative Matrix Factorization Framework for Semi Supervised Learning on Graphs. SDM 2020: 487-495 - [c106]Tarun Kumar, K. Darwin, Srinivasan Parthasarathy, Balaraman Ravindran:
HPRA: Hyperedge Prediction using Resource Allocation. WebSci 2020: 135-143 - [i66]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
SEERL: Sample Efficient Ensemble Reinforcement Learning. CoRR abs/2001.05209 (2020) - [i65]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks. CoRR abs/2002.00786 (2020) - [i64]Sanchari Sen, Balaraman Ravindran, Anand Raghunathan:
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks. CoRR abs/2004.10162 (2020) - [i63]Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Towards Transparent and Explainable Attention Models. CoRR abs/2004.14243 (2020) - [i62]Sravan Mylavarapu, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Balaraman Ravindran, Anoop M. Namboodiri:
Understanding Dynamic Scenes using Graph Convolution Networks. CoRR abs/2005.04437 (2020) - [i61]Nikita Moghe, Priyesh Vijayan, Balaraman Ravindran, Mitesh M. Khapra:
On Incorporating Structural Information to improve Dialogue Response Generation. CoRR abs/2005.14315 (2020) - [i60]Nazneen N. Sultana, Hardik Meisheri, Vinita Baniwal, Somjit Nath, Balaraman Ravindran, Harshad Khadilkar:
Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains. CoRR abs/2006.04037 (2020) - [i59]Siddharth Nishtala, Harshavardhan Kamarthi, Divy Thakkar, Dhyanesh Narayanan, Anirudh Grama, Ramesh Padmanabhan, Neha Madhiwalla, Suresh Chaudhary, Balaraman Ravindran, Milind Tambe:
Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement. CoRR abs/2006.07590 (2020) - [i58]Tarun Kumar, K. Darwin, Srinivasan Parthasarathy, Balaraman Ravindran:
HPRA: Hyperedge Prediction using Resource Allocation. CoRR abs/2006.11070 (2020) - [i57]Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran:
A Causal Linear Model to Quantify Edge Unfairness for Unfair Edge Prioritization and Discrimination Removal. CoRR abs/2007.05516 (2020) - [i56]Siddharth Nayak, Balaraman Ravindran:
Reinforcement Learning for Improving Object Detection. CoRR abs/2008.08005 (2020) - [i55]Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, Balaraman Ravindran:
MADRaS : Multi Agent Driving Simulator. CoRR abs/2010.00993 (2020) - [i54]Anand A. Rajasekar, Karthik Raman, Balaraman Ravindran:
Goal directed molecule generation using Monte Carlo Tree Search. CoRR abs/2010.16399 (2020) - [i53]Deepak Maurya, Balaraman Ravindran:
Hypergraph Partitioning using Tensor Eigenvalue Decomposition. CoRR abs/2011.07683 (2020) - [i52]Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran:
Relational Boosted Bandits. CoRR abs/2012.09220 (2020) - [i51]Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe:
Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. CoRR abs/2012.10389 (2020)
2010 – 2019
- 2019
- [j13]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Studying the plasticity in deep convolutional neural networks using random pruning. Mach. Vis. Appl. 30(2): 203-216 (2019) - [c105]Manan Tomar, Akhil Sathuluri, Balaraman Ravindran:
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. AAAI 2019: 10053-10054 - [c104]Sai Kiran Narayanaswami, Balaraman Ravindran, Venkatesh Ramaiyan:
Generalized random Surfer-Pair models. ASONAM 2019: 452-455 - [c103]Vaibhav Gupta, Daksh Anand, Praveen Paruchuri, Balaraman Ravindran:
Advice Replay Approach for Richer Knowledge Transfer in Teacher Student Framework. AAMAS 2019: 1997-1999 - [c102]Manan Tomar, Akhil Sathuluri, Balaraman Ravindran:
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. AAMAS 2019: 2226-2228 - [c101]Athindran Ramesh Kumar, Balaraman Ravindran, Anand Raghunathan:
Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing. COMAD/CODS 2019: 150-156 - [c100]Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran:
A New Measure of Modularity in Hypergraphs: Theoretical Insights and Implications for Effective Clustering. COMPLEX NETWORKS (1) 2019: 286-297 - [c99]Manju Manohar Manjalavil, Gitakrishnan Ramadurai, Balaraman Ravindran:
Temporal Analysis of a Bus Transit Network. COMPLEX NETWORKS (2) 2019: 944-954 - [c98]Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Let's Ask Again: Refine Network for Automatic Question Generation. EMNLP/IJCNLP (1) 2019: 3312-3321 - [c97]Rahul Ramesh, Manan Tomar, Balaraman Ravindran:
Successor Options: An Option Discovery Framework for Reinforcement Learning. IJCAI 2019: 3304-3310 - [c96]Revanth Reddy, Sarath Chandar, Balaraman Ravindran:
Edge Replacement Grammars : A Formal Language Approach for Generating Graphs. SDM 2019: 351-359 - [i50]Sai Kiran Narayanaswami, Nandan Sudarsanam, Balaraman Ravindran:
An Active Learning Framework for Efficient Robust Policy Search. CoRR abs/1901.00117 (2019) - [i49]Harish Kumar, Balaraman Ravindran:
Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning. CoRR abs/1902.01973 (2019) - [i48]Revanth Reddy, Sarath Chandar, Balaraman Ravindran:
Edge Replacement Grammars: A Formal Language Approach for Generating Graphs. CoRR abs/1902.07159 (2019) - [i47]Saket Gurukar, Priyesh Vijayan, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, Balaraman Ravindran, Srinivasan Parthasarathy:
Network Representation Learning: Consolidation and Renewed Bearing. CoRR abs/1905.00987 (2019) - [i46]Abhishek Ghose, Balaraman Ravindran:
Optimal Resampling for Learning Small Models. CoRR abs/1905.01520 (2019) - [i45]Rahul Ramesh, Manan Tomar, Balaraman Ravindran:
Successor Options: An Option Discovery Framework for Reinforcement Learning. CoRR abs/1905.05731 (2019) - [i44]Manan Tomar, Akhil Sathuluri, Balaraman Ravindran:
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. CoRR abs/1905.07193 (2019) - [i43]Abhishek Ghose, Balaraman Ravindran:
Learning Interpretable Models Using an Oracle. CoRR abs/1906.06852 (2019) - [i42]Anirban Santara, Rishabh Madan, Balaraman Ravindran, Pabitra Mitra:
ExTra: Transfer-guided Exploration. CoRR abs/1906.11785 (2019) - [i41]Sai Kiran Narayanaswami, Balaraman Ravindran, Venkatesh Ramaiyan:
Generalized Random Surfer-Pair Models. CoRR abs/1907.01420 (2019) - [i40]Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe:
Learning policies for Social network discovery with Reinforcement learning. CoRR abs/1907.11625 (2019) - [i39]Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran:
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning. CoRR abs/1909.04134 (2019) - [i38]Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran:
Let's Ask Again: Refine Network for Automatic Question Generation. CoRR abs/1909.05355 (2019) - [i37]Hardik Meisheri, Vinita Baniwal, Nazneen N. Sultana, Balaraman Ravindran, Harshad Khadilkar:
Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems. CoRR abs/1910.00211 (2019) - 2018
- [j12]Nandan Sudarsanam, Balaraman Ravindran:
Using Linear Stochastic Bandits to extend traditional offline Designed Experiments to online settings. Comput. Ind. Eng. 115: 471-485 (2018) - [j11]Dibu John Philip, Nandan Sudarsanam, Balaraman Ravindran:
Improved Insights on Financial Health through Partially Constrained Hidden Markov Model Clustering on Loan Repayment Data. Data Base 49(3): 98-113 (2018) - [c95]Subhojyoti Mukherjee, K. P. Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Efficient-UCBV: An Almost Optimal Algorithm Using Variance Estimates. AAAI 2018: 6417-6424 - [c94]Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
RAIL: Risk-Averse Imitation Learning. AAMAS 2018: 2062-2063 - [c93]Sudarsun Santhiappan, Jeshuren Chelladurai, Balaraman Ravindran:
A novel topic modeling based weighting framework for class imbalance learning. COMAD/CODS 2018: 20-29 - [c92]Chandramohan T. N, Balaraman Ravindran:
A neural attention based approach for clickstream mining. COMAD/CODS 2018: 118-127 - [c91]Deepak Mittal, Avinash Reddy, Gitakrishnan Ramadurai, Kaushik Mitra, Balaraman Ravindran:
Training a deep learning architecture for vehicle detection using limited heterogeneous traffic data. COMSNETS 2018: 589-294 - [c90]Dibu John Philip, Nandan Sudarsanam, Balaraman Ravindran:
A Partial Parameter HMM Based Clustering on Loan Repayment Data: Insights into Financial Behavior and Intent to Repay. HICSS 2018: 1-10 - [c89]Balaraman Ravindran:
Looking Under the Hood of Deep Neural Networks. HiPC 2018: 1 - [c88]Sahil Sharma, Ashutosh Kumar Jha, Parikshit Hegde, Balaraman Ravindran:
Learning to Multi-Task by Active Sampling. ICLR (Poster) 2018 - [c87]Vignesh Prasad, Karmesh Yadav, Rohitashva Singh Saurabh, Swapnil Daga, Nahas Pareekutty, K. Madhava Krishna, Balaraman Ravindran, Brojeshwar Bhowmick:
Learning to Prevent Monocular SLAM Failure using Reinforcement Learning. ICVGIP 2018: 47:1-47:9 - [c86]Meha Kaushik, Vignesh Prasad, K. Madhava Krishna, Balaraman Ravindran:
Overtaking Maneuvers in Simulated Highway Driving using Deep Reinforcement Learning. Intelligent Vehicles Symposium 2018: 1885-1890 - [c85]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks. WACV 2018: 848-857 - [i36]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks. CoRR abs/1801.10447 (2018) - [i35]Parijat Dewangan, S. Phani Teja, K. Madhava Krishna, Abhishek Sarkar, Balaraman Ravindran:
DiGrad: Multi-Task Reinforcement Learning with Shared Actions. CoRR abs/1802.10463 (2018) - [i34]Ghulam Ahmed Ansari, Sagar J. P, Sarath Chandar, Balaraman Ravindran:
Language Expansion In Text-Based Games. CoRR abs/1805.07274 (2018) - [i33]Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Balaraman Ravindran:
HOPF: Higher Order Propagation Framework for Deep Collective Classification. CoRR abs/1805.12421 (2018) - [i32]Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Balaraman Ravindran:
Fusion Graph Convolutional Networks. CoRR abs/1805.12528 (2018) - [i31]Athindran Ramesh Kumar, Balaraman Ravindran, Anand Raghunathan:
Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing. CoRR abs/1809.01701 (2018) - [i30]Ameet Deshpande, Harshavardhan P. K, Balaraman Ravindran:
Discovering hierarchies using Imitation Learning from hierarchy aware policies. CoRR abs/1812.00225 (2018) - [i29]Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra, Balaraman Ravindran:
Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning. CoRR abs/1812.10240 (2018) - [i28]Tarun Kumar, Sankaran Vaidyanathan, Harini Ananthapadmanabhan, Srinivasan Parthasarathy, Balaraman Ravindran:
Hypergraph Clustering: A Modularity Maximization Approach. CoRR abs/1812.10869 (2018) - 2017
- [c84]Aravind S. Lakshminarayanan, Sahil Sharma, Balaraman Ravindran:
Dynamic Action Repetition for Deep Reinforcement Learning. AAAI 2017: 2133-2139 - [c83]Preksha Nema, Mitesh M. Khapra, Anirban Laha, Balaraman Ravindran:
Diversity driven attention model for query-based abstractive summarization. ACL (1) 2017: 1063-1072 - [c82]Prathamesh Deshpande, Balaraman Ravindran:
MCEIL: An Improved Scoring Function for Overlapping Community Detection using Seed Expansion Methods. ASONAM 2017: 652-659 - [c81]Vignesh Prasad, Rishabh Jangir, Balaraman Ravindran, K. Madhava Krishna:
Data Driven Strategies for Active Monocular SLAM using Inverse Reinforcement Learning. AAMAS 2017: 1697-1699 - [c80]Akash Jain, Rupesh Nasre, Balaraman Ravindran:
DCEIL: Distributed Community Detection with the CEIL Score. HPCC/SmartCity/DSS 2017: 146-153 - [c79]Pratik Vinay Gupte, Balaraman Ravindran, Srinivasan Parthasarathy:
Role Discovery in Graphs Using Global Features: Algorithms, Applications and a Novel Evaluation Strategy. ICDE 2017: 771-782 - [c78]Janarthanan Rajendran, Aravind S. Lakshminarayanan, Mitesh M. Khapra, P. Prasanna, Balaraman Ravindran:
Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain. ICLR (Poster) 2017 - [c77]Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran, Sergey Levine:
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. ICLR (Poster) 2017 - [c76]Sahil Sharma, Aravind S. Lakshminarayanan, Balaraman Ravindran:
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning. ICLR (Poster) 2017 - [c75]Sahil Sharma, Balaraman Ravindran:
Online Multi-Task Learning Using Active Sampling. ICLR (Workshop) 2017 - [c74]Subhojyoti Mukherjee, Kolar Purushothama Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Thresholding Bandits with Augmented UCB. IJCAI 2017: 2515-2521 - [c73]Girraj Pahariya, Balaraman Ravindran, Sukhendu Das:
Dynamic Class Learning Approach for Smart CBIR. NCVPRIPG 2017: 327-337 - [i27]Sahil Sharma, Balaraman Ravindran:
Online Multi-Task Learning Using Active Sampling. CoRR abs/1702.06053 (2017) - [i26]Sahil Sharma, Aravind S. Lakshminarayanan, Balaraman Ravindran:
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning. CoRR abs/1702.06054 (2017) - [i25]Sanjay Ganapathy, Swagath Venkataramani, Balaraman Ravindran, Anand Raghunathan:
DyVEDeep: Dynamic Variable Effort Deep Neural Networks. CoRR abs/1704.01137 (2017) - [i24]Subhojyoti Mukherjee, Kolar Purushothama Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Thresholding Bandits with Augmented UCB. CoRR abs/1704.02281 (2017) - [i23]Preksha Nema, Mitesh M. Khapra, Anirban Laha, Balaraman Ravindran:
Diversity driven Attention Model for Query-based Abstractive Summarization. CoRR abs/1704.08300 (2017) - [i22]Sahil Sharma, Aravind Suresh, Rahul Ramesh, Balaraman Ravindran:
Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning. CoRR abs/1705.07269 (2017) - [i21]Sahil Sharma, Girish Raguvir J, Srivatsan Ramesh, Balaraman Ravindran:
Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement Learning. CoRR abs/1705.07445 (2017) - [i20]Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
RAIL: Risk-Averse Imitation Learning. CoRR abs/1707.06658 (2017) - [i19]Rakesh R. Menon, Balaraman Ravindran:
Shared Learning : Enhancing Reinforcement in $Q$-Ensembles. CoRR abs/1709.04909 (2017) - [i18]Subhojyoti Mukherjee, K. P. Naveen, Nandan Sudarsanam, Balaraman Ravindran:
Efficient-UCBV: An Almost Optimal Algorithm using Variance Estimates. CoRR abs/1711.03591 (2017) - [i17]Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran:
Rate of Change Analysis for Interestingness Measures. CoRR abs/1712.05193 (2017) - 2016
- [j10]Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran:
Correlational Neural Networks. Neural Comput. 28(2): 257-285 (2016) - [c72]Varun Gangal, Abhishek Narwekar, Balaraman Ravindran, Ramasuri Narayanam:
Trust and Distrust Across Coalitions: Shapley Value Based Centrality Measures for Signed Networks (Student Abstract Version). AAAI 2016: 4212- - [c71]Varun Gangal, Balaraman Ravindran, Ramasuri Narayanam:
HEMI: Hyperedge Majority Influence Maximization. SocInf@IJCAI 2016: 38-47 - [c70]Janarthanan Rajendran, Mitesh M. Khapra, Sarath Chandar, Balaraman Ravindran:
Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning. HLT-NAACL 2016: 171-181 - [e4]Amol Deshpande, Balaraman Ravindran, Sayan Ranu:
21st International Conference on Management of Data, COMAD 2016, Pune, India, March 11-13, 2016. Computer Society of India 2016 [contents] - [i16]Nandan Sudarsanam, Balaraman Ravindran:
Linear Bandit algorithms using the Bootstrap. CoRR abs/1605.01185 (2016) - [i15]Ramnandan Krishnamurthy, Aravind S. Lakshminarayanan, Peeyush Kumar, Balaraman Ravindran:
Hierarchical Reinforcement Learning using Spatio-Temporal Abstractions and Deep Neural Networks. CoRR abs/1605.05359 (2016) - [i14]Aravind S. Lakshminarayanan, Sahil Sharma, Balaraman Ravindran:
Dynamic Frame skip Deep Q Network. CoRR abs/1605.05365 (2016) - [i13]Varun Gangal, Balaraman Ravindran, Ramasuri Narayanam:
HEMI: Hyperedge Majority Influence Maximization. CoRR abs/1606.05065 (2016) - [i12]Vignesh Prasad, Saurabh Singh, Nahas Pareekutty, Balaraman Ravindran, K. Madhava Krishna:
SLAM-Safe Planner: Preventing Monocular SLAM Failure using Reinforcement Learning. CoRR abs/1607.07558 (2016) - [i11]Aravind Rajeswaran, Sarvjeet Ghotra, Sergey Levine, Balaraman Ravindran:
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. CoRR abs/1610.01283 (2016) - [i10]Sai Praveen Bangaru, J. S. Suhas, Balaraman Ravindran:
Exploration for Multi-task Reinforcement Learning with Deep Generative Models. CoRR abs/1611.09894 (2016) - 2015
- [j9]Pragathi Priyadharsini Balasubramani, V. Srinivasa Chakravarthy, Balaraman Ravindran, Ahmed A. Moustafa:
A network model of basal ganglia for understanding the roles of dopamine and serotonin in reward-punishment-risk based decision making. Frontiers Comput. Neurosci. 9: 76 (2015) - [j8]K. S. Gayathri, Susan Elias, Balaraman Ravindran:
Hierarchical activity recognition for dementia care using Markov Logic Network. Pers. Ubiquitous Comput. 19(2): 271-285 (2015) - [c69]Ramakumar Pasumarthi, Ramasuri Narayanam, Balaraman Ravindran:
Near Optimal Strategies for Targeted Marketing in Social Networks. AAMAS 2015: 1679-1680 - [c68]Sangameshwar Patil, Balaraman Ravindran:
Active Learning Based Weak Supervision for Textual Survey Response Classification. CICLing (2) 2015: 309-320 - [c67]Sanjukta Roy, Balaraman Ravindran:
Measuring network centrality using hypergraphs. CODS 2015: 59-68 - [c66]Subendhu Rongali, A. P. Sarath Chandar, Balaraman Ravindran:
From multiple views to single view: a neural network approach. CODS 2015: 104-109 - [c65]Avijit Saha, Ayan Acharya, Balaraman Ravindran, Joydeep Ghosh:
Nonparametric Poisson Factorization Machine. ICDM 2015: 967-972 - [c64]Vishnu Sankar, Balaraman Ravindran, S. Shivashankar:
CEIL: A Scalable, Resolution Limit Free Approach for Detecting Communities in Large Networks. IJCAI 2015: 2097-2103 - [c63]Sai Nageswar Satchidanand, Harini Ananthapadmanaban, Balaraman Ravindran:
Extended Discriminative Random Walk: A Hypergraph Approach to Multi-View Multi-Relational Transductive Learning. IJCAI 2015: 3791-3797 - [c62]Avijit Saha, Rishabh Misra, Balaraman Ravindran:
Scalable Bayesian Matrix Factorization. MUSE@PKDD/ECML 2015: 43-54 - [c61]Saket Gurukar, Sayan Ranu, Balaraman Ravindran:
COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks. SIGMOD Conference 2015: 475-489 - [i9]Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran:
Correlational Neural Networks. CoRR abs/1504.07225 (2015) - [i8]Abhinav Garlapati, Aditi Raghunathan, Vaishnavh Nagarajan, Balaraman Ravindran:
A Reinforcement Learning Approach to Online Learning of Decision Trees. CoRR abs/1507.06923 (2015) - [i7]P. Prasanna, Sarath Chandar, Balaraman Ravindran:
TSEB: More Efficient Thompson Sampling for Policy Learning. CoRR abs/1510.02874 (2015) - [i6]Janarthanan Rajendran, P. Prasanna, Balaraman Ravindran, Mitesh M. Khapra:
ADAAPT: A Deep Architecture for Adaptive Policy Transfer from Multiple Sources. CoRR abs/1510.02879 (2015) - [i5]Janarthanan Rajendran, Mitesh M. Khapra, Sarath Chandar, Balaraman Ravindran:
Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning. CoRR abs/1510.03519 (2015) - 2014
- [j7]Pragathi Priyadharsini Balasubramani, V. Srinivasa Chakravarthy, Balaraman Ravindran, Ahmed A. Moustafa:
An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning. Frontiers Comput. Neurosci. 8: 47 (2014) - [c60]Priyesh Vijayan, Shivashankar Subramanian, Balaraman Ravindran:
Multi-label collective classification in multi-attribute multi-relational network data. ASONAM 2014: 509-514 - [c59]Saket Gurukar, Balaraman Ravindran:
Temporal analysis of telecom call graphs. COMSNETS 2014: 1-6 - [c58]Sai Nageswar Satchidanand, Siddharth Kumar Jain, Amit Maurya, Balaraman Ravindran:
Studying Indian Railways Network using hypergraphs. COMSNETS 2014: 1-6 - [c57]Manimaran Sivasamy Sivamurugan, Balaraman Ravindran:
RRTPI: Policy iteration on continuous domains using rapidly-exploring random trees. ICRA 2014: 4362-4367 - [c56]A. P. Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas C. Raykar, Amrita Saha:
An Autoencoder Approach to Learning Bilingual Word Representations. NIPS 2014: 1853-1861 - [c55]Addwiteey Chrungoo, S. S. Manimaran, Balaraman Ravindran:
Activity Recognition for Natural Human Robot Interaction. ICSR 2014: 84-94 - [e3]Balaraman Ravindran, Kamalakar Karlapalem:
Proceedings of the 1st IKDD Conference on Data Sciences, Delhi, India, March 21 - 23, 2014. ACM 2014, ISBN 978-1-4503-2475-5 [contents] - [i4]Tomasz Pawel Michalak, Aadithya V. Karthik, Piotr L. Szczepanski, Balaraman Ravindran, Nicholas R. Jennings:
Efficient Computation of the Shapley Value for Game-Theoretic Network Centrality. CoRR abs/1402.0567 (2014) - [i3]A. P. Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas C. Raykar, Amrita Saha:
An Autoencoder Approach to Learning Bilingual Word Representations. CoRR abs/1402.1454 (2014) - [i2]Pratik Vinay Gupte, Balaraman Ravindran:
Scalable Positional Analysis for Studying Evolution of Nodes in Networks. CoRR abs/1402.3797 (2014) - 2013
- [j6]Tomasz P. Michalak, Aadithya V. Karthik, Piotr L. Szczepanski, Balaraman Ravindran, Nicholas R. Jennings:
Efficient Computation of the Shapley Value for Game-Theoretic Network Centrality. J. Artif. Intell. Res. 46: 607-650 (2013) - [c54]Deepak Pai, Balaraman Ravindran, Shyam Rajagopalan, Ramesh Srinivasaraghavan:
Automated faceted reporting for web analytics. Web-KRM@CIKM 2013: 9-16 - [c53]Balaji Vasan Srinivasan, Anandhavelu Natarajan, Ritwik Sinha, Vineet Gupta, Shriram Revankar, Balaraman Ravindran:
Will your facebook post be engaging? UEO@CIKM 2013: 25-28 - [c52]Lakshmi Ramachandran, Balaraman Ravindran, Edward F. Gehringer:
Determining Review Coverage by Extracting Topic Sentences Using A Graph-based Clustering Approach. EDM 2013: 346-347 - [c51]Debarun Kar, Anand Kumar, Sutanu Chakraborti, Balaraman Ravindran:
iCaseViz: Learning Case Similarities through Interaction with a Case Base Visualizer. ICCBR 2013: 203-217 - [c50]Nilanjan Banerjee, Dipanjan Chakraborty, Anupam Joshi, Sumit Mittal, Angshu Rai, Balaraman Ravindran:
Detection of Real-Time Intentions from Micro-blogs. MobiQuitous 2013: 116-128 - [c49]Swapna Raj Prabakara Raj, Balaraman Ravindran:
Incremental Constrained Clustering: A Decision Theoretic Approach. PAKDD Workshops 2013: 475-486 - 2012
- [c48]Arun Tejasvi Chaganty, Prateek Gaur, Balaraman Ravindran:
Learning in a small world. AAMAS 2012: 391-397 - [c47]Saradindu Kar, Deepak Vijayakeerthi, Ashish V. Tendulkar, Balaraman Ravindran:
Functional site prediction by exploiting correlations between labels of interacting residues. BCB 2012: 76-83 - [c46]R. Rangadurai Karthick, Vipul P. Hattiwale, Balaraman Ravindran:
Adaptive network intrusion detection system using a hybrid approach. COMSNETS 2012: 1-7 - [c45]Pradyot Korupolu V. N., Manimaran Sivasamy Sivamurugan, Balaraman Ravindran:
Instructing a Reinforcement Learner. FLAIRS 2012 - [c44]Pragathi Priyadharsini Balasubramani, Balaraman Ravindran, V. Srinivasa Chakravarthy:
Understanding the Role of Serotonin in Basal Ganglia through a Unified Model. ICANN (1) 2012: 467-473 - [c43]Debarun Kar, Sutanu Chakraborti, Balaraman Ravindran:
Feature Weighting and Confidence Based Prediction for Case Based Reasoning Systems. ICCBR 2012: 211-225 - [c42]José I. Nuñez-Varela, Balaraman Ravindran, Jeremy L. Wyatt:
Where do i look now? Gaze allocation during visually guided manipulation. ICRA 2012: 4444-4449 - [c41]Nilanjan Banerjee, Dipanjan Chakraborty, Anupam Joshi, Sumit Mittal, Angshu Rai, Balaraman Ravindran:
Towards Analyzing Micro-Blogs for Detection and Classification of Real-Time Intentions. ICWSM 2012 - [c40]José I. Nuñez-Varela, Balaraman Ravindran, Jeremy L. Wyatt:
Gaze Allocation Analysis for a Visually Guided Manipulation Task. SAB 2012: 44-53 - [c39]Pradyot Korupolu V. N., S. S. Manimaran, Balaraman Ravindran, Sriraam Natarajan:
Integrating Human Instructions and Reinforcement Learners: An SRL Approach. StarAI@UAI 2012 - [i1]Ananda Narayanan B., Balaraman Ravindran:
Fractional Moments on Bandit Problems. CoRR abs/1202.3750 (2012) - 2011
- [j5]S. Shivashankar, S. Srivathsan, Balaraman Ravindran, Ashish V. Tendulkar:
Multi-view methods for protein structure comparison using latent dirichlet allocation. Bioinform. 27(13): 61-68 (2011) - [j4]K. N. Magdoom, Deepak Subramanian, V. Srinivasa Chakravarthy, Balaraman Ravindran, Shun-ichi Amari, N. Meenakshisundaram:
Modeling Basal Ganglia for Understanding Parkinsonian Reaching Movements. Neural Comput. 23(2): 477-516 (2011) - [c38]Rajagopalan Vijayasarathy, Serugudi Venkataraman Raghavan, Balaraman Ravindran:
A system approach to network modeling for DDoS detection using a Naìve Bayesian classifier. COMSNETS 2011: 1-10 - [c37]Munu Sairamesh, Balaraman Ravindran:
Options with Exceptions. EWRL 2011: 165-176 - [c36]Ankit Malpani, Balaraman Ravindran, Hema A. Murthy:
Personalized Intelligent Tutoring System Using Reinforcement Learning. FLAIRS 2011 - [c35]Prabakararaj Swapna Raj, Balaraman Ravindran:
Utility Driven Clustering. FLAIRS 2011 - [c34]Ananda Narayanan B., Balaraman Ravindran:
Fractional Moments on Bandit Problems. UAI 2011: 531-538 - 2010
- [j3]M. Saravanan, Balaraman Ravindran:
Identification of Rhetorical Roles for Segmentation and Summarization of a Legal Judgment. Artif. Intell. Law 18(1): 45-76 (2010) - [c33]Aadithya V. Karthik, Balaraman Ravindran:
Game theoretic network centrality: exact formulas and efficient algorithms. AAMAS 2010: 1459-1460 - [c32]S. Shivashankar, Balaraman Ravindran:
Multi Grain Sentiment Analysis using Collective Classification. ECAI 2010: 823-828 - [c31]Prabakararaj Swapna Raj, Balaraman Ravindran:
Mining Actionable Patterns. FLAIRS 2010 - [c30]Yousuf Aboobaker Sait, Balaraman Ravindran:
Visual Object Detection using Frequent Pattern Mining. FLAIRS 2010 - [c29]Maya Manaithunai, V. Srinivasa Chakravarthy, Balaraman Ravindran:
An Oscillatory Neural Network Model for Birdsong Learning and Generation. ICANN (2) 2010: 210-215 - [c28]Aswin N. Raghavan, Harini Ananthapadmanaban, Manimaran Sivasamy Sivamurugan, Balaraman Ravindran:
Accurate mobile robot localization in indoor environments using bluetooth. ICRA 2010: 4391-4396 - [c27]Balaji Lakshmanan, Balaraman Ravindran:
Transfer learning across heterogeneous robots with action sequence mapping. IROS 2010: 3251-3256 - [c26]Aadithya V. Karthik, Balaraman Ravindran, Tomasz P. Michalak, Nicholas R. Jennings:
Efficient Computation of the Shapley Value for Centrality in Networks. WINE 2010: 1-13 - [e2]Mohammed Javeed Zaki, Jeffrey Xu Yu, Balaraman Ravindran, Vikram Pudi:
Advances in Knowledge Discovery and Data Mining, 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part I. Lecture Notes in Computer Science 6118, Springer 2010, ISBN 978-3-642-13656-6 [contents] - [e1]Mohammed Javeed Zaki, Jeffrey Xu Yu, Balaraman Ravindran, Vikram Pudi:
Advances in Knowledge Discovery and Data Mining, 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part II. Lecture Notes in Computer Science 6119, Springer 2010, ISBN 978-3-642-13671-9 [contents]
2000 – 2009
- 2009
- [j2]M. Saravanan, Balaraman Ravindran, S. Raman:
Improving legal information retrieval using an ontological framework. Artif. Intell. Law 17(2): 101-124 (2009) - [c25]Jyotika Bahuguna, Balaraman Ravindran, K. Madhava Krishna:
MDP based active localization for multiple robots. CASE 2009: 635-640 - [c24]Kiran Kate, Balaraman Ravindran:
Epsilon Equitable Partition: A positional analysis method for large social networks. COMAD 2009 - 2008
- [c23]Swapna Raj Prabakara Raj, Balaraman Ravindran:
Personalized Web-page Rendering System. COMAD 2008: 30-39 - [c22]Sriram Raghavan, Balaraman Ravindran:
Successive refinement algorithms for distributed area coverage using mobile robots. Bangalore Compute Conf. 2008: 20 - [c21]Aniket Ray, Vikas Kumar, Balaraman Ravindran, Lingam Gopal, Aditya Verma:
Machine Learning to Predict the Incidence of Retinopathy of Prematurity. FLAIRS 2008: 300-305 - [c20]P. Swaminathan, Balaraman Ravindran:
Co-SOFT-Clustering: An Information Theoretic Approach to Obtain Overlapping Clusters from Co-Occurrence Data. FLAIRS 2008: 320-321 - [c19]Rachit Arora, Balaraman Ravindran:
Latent Dirichlet Allocation and Singular Value Decomposition Based Multi-document Summarization. ICDM 2008: 713-718 - [c18]Shravan Matthur Narayanamurthy, Balaraman Ravindran:
On the hardness of finding symmetries in Markov decision processes. ICML 2008: 688-695 - [c17]Dinakar Jayarajan, Dipti Deodhare, Balaraman Ravindran:
Lexical Chains as Document Features. IJCNLP 2008: 111-117 - [c16]M. Saravanan, Balaraman Ravindran, S. Raman:
Automatic Identification of Rhetorical Roles using Conditional Random Fields for Legal Document Summarization. IJCNLP 2008: 481-488 - [c15]Rachit Arora, Balaraman Ravindran:
Latent dirichlet allocation based multi-document summarization. AND 2008: 91-97 - 2007
- [c14]Sriram Raghavan, Balaraman Ravindran:
Profiling Pseudonet Architecture for Coordinating Mobile Robots. COMSWARE 2007 - [c13]B. H. Sreenivasa Sarma, Balaraman Ravindran:
Intelligent Tutoring Systems using Reinforcement Learning to teach Autistic Students. HOIT 2007: 65-78 - [c12]Balaraman Ravindran, Andrew G. Barto, Vimal Mathew:
Deictic Option Schemas. IJCAI 2007: 1023-1028 - [c11]Pranjal Awasthi, Aakanksha Gagrani, Balaraman Ravindran:
Image Modeling Using Tree Structured Conditional Random Fields. IJCAI 2007: 2060-2065 - [c10]Shravan Matthur Narayanamurthy, Balaraman Ravindran:
Efficiently Exploiting Symmetries in Real Time Dynamic Programming. IJCAI 2007: 2556-2561 - [c9]M. Saravanan, Balaraman Ravindran, S. Raman:
Using Legal Ontology for Query Enhancement in Generating a Document Summary. JURIX 2007: 171-172 - [c8]Sriram Raghavan, Balaraman Ravindran:
Homogeneous Hierarchical Composition of Areas in Multi-robot Area Coverage. SARA 2007: 300-313 - 2006
- [j1]M. Saravanan, S. Raman, Balaraman Ravindran:
A Probabilistic Approach to Multi-Document Summarization for Generating a Tiled Summary. Int. J. Comput. Intell. Appl. 6(2): 231-243 (2006) - [c7]Aakanksha Gagrani, Lalit Gupta, Balaraman Ravindran, Sukhendu Das, Pinaki Roychowdhury, V. K. Panchal:
A Hierarchical Approach to Landform Classification of Satellite Images Using a Fusion Strategy. ICVGIP 2006: 140-151 - [c6]M. Saravanan, Balaraman Ravindran, S. Raman:
Improving Legal Document Summarization Using Graphical Models. JURIX 2006: 51-60 - 2005
- [c5]R. Manimegalai, E. Siva Soumya, Vaishnavi Muralidharan, Balaraman Ravindran, V. Kamakoti, Dinesh Bhatia:
Placement and Routing for 3D-FPGAs Using Reinforcement Learning and Support Vector Machines. VLSI Design 2005: 451-456 - 2003
- [c4]Balaraman Ravindran, Andrew G. Barto:
Relativized Options: Choosing the Right Transformation. ICML 2003: 608-615 - [c3]Balaraman Ravindran, Andrew G. Barto:
SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes. IJCAI 2003: 1011-1018 - 2002
- [c2]Balaraman Ravindran, Andrew G. Barto:
Model Minimization in Hierarchical Reinforcement Learning. SARA 2002: 196-211
1990 – 1999
- 1998
- [c1]Richard S. Sutton, Satinder Singh, Doina Precup, Balaraman Ravindran:
Improved Switching among Temporally Abstract Actions. NIPS 1998: 1066-1072
Coauthor Index
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