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2020 – today
- 2024
[c46]Vedang Asgaonkar, Aditya Jain, Abir De:
Generator Assisted Mixture of Experts for Feature Acquisition in Batch. AAAI 2024: 10927-10934- [c45]Lokesh Nagalapatti, Akshay Iyer, Abir De, Sunita Sarawagi:
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing. AAAI 2024: 14397-14404 - [i34]Lokesh Nagalapatti, Akshay Iyer, Abir De, Sunita Sarawagi:
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing. CoRR abs/2401.15447 (2024) - [i33]Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal, Ashish Tendulkar, Rishabh K. Iyer, Abir De:
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks. CoRR abs/2409.12255 (2024) - 2023
- [c44]Paramita Koley, Harshavardhan Alimi
, Shrey Singla, Sourangshu Bhattacharya, Niloy Ganguly, Abir De:
Differentiable Change-point Detection With Temporal Point Processes. AISTATS 2023: 6940-6955 - [c43]Parth Vipul Sangani, Arjun Shashank Kashettiwar, Pritish Chakraborty, Bhuvan Reddy Gangula, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer, Abir De:
Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models. ICML 2023: 29950-29970 - [c42]Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal, Ashish Tendulkar, Rishabh K. Iyer, Abir De:
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks. NeurIPS 2023 - [c41]Indradyumna Roy, Rishi Agarwal, Soumen Chakrabarti, Anirban Dasgupta, Abir De:
Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search. NeurIPS 2023 - [c40]Pritish Chakraborty, Sayan Ranu, Krishna Sri Ipsit Mantri, Abir De:
Learning and Maximizing Influence in Social Networks Under Capacity Constraints. WSDM 2023: 733-741 - [i32]Vinayak Gupta, Srikanta Bedathur, Abir De:
Retrieving Continuous Time Event Sequences using Neural Temporal Point Processes with Learnable Hashing. CoRR abs/2307.09613 (2023) - [i31]Vedang Asgaonkar, Aditya Jain, Abir De:
Generator Assisted Mixture of Experts For Feature Acquisition in Batch. CoRR abs/2312.12574 (2023) - 2022
- [j8]Stratis Tsirtsis, Abir De, Lars Lorch, Manuel Gomez-Rodriguez:
Pooled testing of traced contacts under superspreading dynamics. PLoS Comput. Biol. 18(3) (2022) - [j7]Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De:
Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes. ACM Trans. Intell. Syst. Technol. 13(6): 103:1-103:26 (2022) - [j6]Vahid Balazadeh Meresht, Abir De, Adish Singla, Manuel Gomez Rodriguez:
Learning to Switch Among Agents in a Team. Trans. Mach. Learn. Res. 2022 (2022) - [c39]Vinayak Gupta, Srikanta Bedathur, Abir De:
Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences. AAAI 2022: 4005-4013 - [c38]Indradyumna Roy, Venkata Sai Baba Reddy Velugoti, Soumen Chakrabarti, Abir De:
Interpretable Neural Subgraph Matching for Graph Retrieval. AAAI 2022: 8115-8123 - [c37]Tathagat Verma, Abir De, Yateesh Agrawal, Vishwa Vinay, Soumen Chakrabarti:
VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis. ICML 2022: 22168-22183 - [c36]Abir De, Soumen Chakrabarti:
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection. NeurIPS 2022 - [c35]Lokesh Nagalapatti, Guntakanti Sai Koushik, Abir De, Sunita Sarawagi:
Learning Recourse on Instance Environment to Enhance Prediction Accuracy. NeurIPS 2022 - [c34]Indradyumna Roy, Soumen Chakrabarti, Abir De:
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks. NeurIPS 2022 - [i30]Vinayak Gupta, Srikanta Bedathur, Abir De:
Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences. CoRR abs/2202.11485 (2022) - [i29]Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De:
Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes. CoRR abs/2206.12414 (2022) - [i28]Indradyumna Roy, Soumen Chakrabarti, Abir De:
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks. CoRR abs/2210.11020 (2022) - [i27]Abir De, Soumen Chakrabarti:
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection. CoRR abs/2210.11033 (2022) - 2021
- [j5]Paramita Koley, Avirup Saha, Sourangshu Bhattacharya, Niloy Ganguly, Abir De:
Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach. ACM Trans. Knowl. Discov. Data 15(6): 99:1-99:25 (2021) - [c33]Abir De, Soumen Chakrabarti:
Differentially Private Link Prediction with Protected Connections. AAAI 2021: 63-71 - [c32]Abir De, Nastaran Okati, Ali Zarezade, Manuel Gomez Rodriguez:
Classification Under Human Assistance. AAAI 2021: 5905-5913 - [c31]Indradyumna Roy, Abir De, Soumen Chakrabarti:
Adversarial Permutation Guided Node Representations for Link Prediction. AAAI 2021: 9445-9453 - [c30]Abir De:
Invited Tutorial: Human Assisted ML. AIMLSystems 2021: 26:1-26:2 - [c29]Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De:
Learning Temporal Point Processes with Intermittent Observations. AISTATS 2021: 3790-3798 - [c28]Chitrank Gupta, Yash Jain, Abir De, Soumen Chakrabarti:
Integrating Transductive and Inductive Embeddings Improves Link Prediction Accuracy. CIKM 2021: 3043-3047 - [c27]KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer:
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training. ICML 2021: 5464-5474 - [c26]Durga Sivasubramanian, Rishabh K. Iyer, Ganesh Ramakrishnan, Abir De:
Training Data Subset Selection for Regression with Controlled Generalization Error. ICML 2021: 9202-9212 - [c25]Ping Zhang, Rishabh K. Iyer, Ashish Tendulkar, Gaurav Aggarwal, Abir De:
Learning to Select Exogenous Events for Marked Temporal Point Process. NeurIPS 2021: 347-361 - [c24]Nastaran Okati, Abir De, Manuel Gomez-Rodriguez:
Differentiable Learning Under Triage. NeurIPS 2021: 9140-9151 - [c23]Anshul Nasery, Soumyadeep Thakur, Vihari Piratla, Abir De, Sunita Sarawagi:
Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time. NeurIPS 2021: 19198-19209 - [c22]Stratis Tsirtsis, Abir De, Manuel Rodriguez:
Counterfactual Explanations in Sequential Decision Making Under Uncertainty. NeurIPS 2021: 30127-30139 - [c21]Prathamesh Deshpande, Kamlesh Marathe, Abir De, Sunita Sarawagi:
Long Horizon Forecasting with Temporal Point Processes. WSDM 2021: 571-579 - [i26]Prathamesh Deshpande, Kamlesh Marathe, Abir De, Sunita Sarawagi:
Long Horizon Forecasting With Temporal Point Processes. CoRR abs/2101.02815 (2021) - [i25]Paramita Koley, Avirup Saha, Sourangshu Bhattacharya, Niloy Ganguly, Abir De:
Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach. CoRR abs/2102.05954 (2021) - [i24]KrishnaTeja Killamsetty, Durga Sivasubramanian, Baharan Mirzasoleiman, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer:
GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning. CoRR abs/2103.00123 (2021) - [i23]Nastaran Okati, Abir De, Manuel Gomez-Rodriguez:
Differentiable Learning Under Triage. CoRR abs/2103.08902 (2021) - [i22]Durga Sivasubramanian, Rishabh K. Iyer, Ganesh Ramakrishnan, Abir De:
Training Data Subset Selection for Regression with Controlled Generalization Error. CoRR abs/2106.12491 (2021) - [i21]Stratis Tsirtsis, Abir De, Lars Lorch, Manuel Gomez-Rodriguez:
Group Testing under Superspreading Dynamics. CoRR abs/2106.15988 (2021) - [i20]Stratis Tsirtsis, Abir De, Manuel Gomez-Rodriguez:
Counterfactual Explanations in Sequential Decision Making Under Uncertainty. CoRR abs/2107.02776 (2021) - [i19]Anshul Nasery, Soumyadeep Thakur, Vihari Piratla, Abir De, Sunita Sarawagi:
Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time. CoRR abs/2108.06721 (2021) - [i18]Chitrank Gupta, Yash Jain, Abir De, Soumen Chakrabarti:
Integrating Transductive And Inductive Embeddings Improves Link Prediction Accuracy. CoRR abs/2108.10108 (2021) - [i17]Santanu Rathod, Manoj Bhadu, Abir De:
Global Convergence Using Policy Gradient Methods for Model-free Markovian Jump Linear Quadratic Control. CoRR abs/2111.15228 (2021) - 2020
- [j4]Bidisha Samanta, Abir De, Gourhari Jana, Vicenç Gómez, Pratim Kumar Chattaraj, Niloy Ganguly, Manuel Gomez-Rodriguez:
NEVAE: A Deep Generative Model for Molecular Graphs. J. Mach. Learn. Res. 21: 114:1-114:33 (2020) - [c20]Abir De, Paramita Koley, Niloy Ganguly, Manuel Gomez-Rodriguez:
Regression under Human Assistance. AAAI 2020: 2611-2620 - [c19]Kunal Goyal, Utkarsh Gupta, Abir De, Soumen Chakrabarti:
Deep Neural Matching Models for Graph Retrieval. SIGIR 2020: 1701-1704 - [c18]Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez:
On the design of consequential ranking algorithms. UAI 2020: 171-180 - [c17]Abir De, Adish Singla, Utkarsh Upadhyay, Manuel Gomez-Rodriguez:
Can A User Guess What Her Followers Want? WSDM 2020: 142-150 - [i16]Vahid Balazadeh Meresht, Abir De, Adish Singla, Manuel Gomez-Rodriguez:
Learning to Switch Between Machines and Humans. CoRR abs/2002.04258 (2020) - [i15]Abir De, Nastaran Okati, Ali Zarezade, Manuel Gomez-Rodriguez:
Classification Under Human Assistance. CoRR abs/2006.11845 (2020) - [i14]Indradyumna Roy, Abir De, Soumen Chakrabarti:
Adversarial Permutation Guided Node Representations for Link Prediction. CoRR abs/2012.08974 (2020)
2010 – 2019
- 2019
- [j3]Abir De, Sourangshu Bhattacharya, Parantapa Bhattacharya, Niloy Ganguly, Soumen Chakrabarti:
Learning Linear Influence Models in Social Networks from Transient Opinion Dynamics. ACM Trans. Web 13(3): 16:1-16:33 (2019) - [c16]Bidisha Samanta, Abir De, Gourhari Jana, Pratim Kumar Chattaraj, Niloy Ganguly, Manuel Gomez Rodriguez:
NeVAE: A Deep Generative Model for Molecular Graphs. AAAI 2019: 1110-1117 - [c15]Avirup Saha, Niloy Ganguly, Sandip Chakraborty, Abir De:
Learning Network Traffic Dynamics Using Temporal Point Process. INFOCOM 2019: 1927-1935 - [c14]Utkarsh Upadhyay, Abir De, Aasish Pappu, Manuel Gomez-Rodriguez:
On the Complexity of Opinions and Online Discussions. WSDM 2019: 258-266 - [i13]Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez:
Consequential Ranking Algorithms and Long-term Welfare. CoRR abs/1905.05305 (2019) - [i12]Abir De, Soumen Chakrabarti:
Privacy Preserving Link Prediction with Latent Geometric Network Models. CoRR abs/1908.04849 (2019) - [i11]Abir De, Adish Singla, Utkarsh Upadhyay, Manuel Gomez-Rodriguez:
Can A User Anticipate What Her Followers Want? CoRR abs/1909.00440 (2019) - [i10]Abir De, Paramita Koley, Niloy Ganguly, Manuel Gomez-Rodriguez:
Regression Under Human Assistance. CoRR abs/1909.02963 (2019) - 2018
- [c13]Abir De, Sourangshu Bhattacharya, Niloy Ganguly:
Shaping Opinion Dynamics in Social Networks. AAMAS 2018: 1336-1344 - [c12]Avirup Saha, Bidisha Samanta, Niloy Ganguly, Abir De:
CRPP: Competing Recurrent Point Process for Modeling Visibility Dynamics in Information Diffusion. CIKM 2018: 537-546 - [c11]Utkarsh Upadhyay, Abir De, Manuel Gomez Rodriguez:
Deep Reinforcement Learning of Marked Temporal Point Processes. NeurIPS 2018: 3172-3182 - [c10]Abir De, Sourangshu Bhattacharya, Niloy Ganguly:
Demarcating Endogenous and Exogenous Opinion Diffusion Process on Social Networks. WWW 2018: 549-558 - [i9]Bidisha Samanta, Abir De, Niloy Ganguly, Manuel Gomez-Rodriguez:
Designing Random Graph Models Using Variational Autoencoders With Applications to Chemical Design. CoRR abs/1802.05283 (2018) - [i8]Utkarsh Upadhyay, Abir De, Aasish Pappu, Manuel Gomez-Rodriguez:
On the Complexity of Opinions and Online Discussions. CoRR abs/1802.06807 (2018) - [i7]Ali Zarezade, Abir De, Utkarsh Upadhyay, Hamid R. Rabiee, Manuel Gomez-Rodriguez:
Steering Social Activity: A Stochastic Optimal Control Point Of View. CoRR abs/1802.07244 (2018) - [i6]Utkarsh Upadhyay, Abir De, Manuel Gomez-Rodriguez:
Deep Reinforcement Learning of Marked Temporal Point Processes. CoRR abs/1805.09360 (2018) - [i5]Lars Lorch, Abir De, Samir Bhatt, William Trouleau, Utkarsh Upadhyay, Manuel Gomez-Rodriguez:
Stochastic Optimal Control of Epidemic Processes in Networks. CoRR abs/1810.13043 (2018) - 2017
- [j2]Ali Zarezade, Abir De, Utkarsh Upadhyay, Hamid R. Rabiee, Manuel Gomez-Rodriguez:
Steering Social Activity: A Stochastic Optimal Control Point Of View. J. Mach. Learn. Res. 18: 205:1-205:35 (2017) - [c9]Bhushan Kulkarni, Sumit Agarwal, Abir De, Sourangshu Bhattacharya, Niloy Ganguly:
SLANT+: A Nonlinear Model for Opinion Dynamics in Social Networks. ICDM 2017: 931-936 - [c8]Bidisha Samanta, Abir De, Abhijnan Chakraborty, Niloy Ganguly:
LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity. IJCAI 2017: 2679-2685 - [c7]Bidisha Samanta, Abir De, Niloy Ganguly:
STRM: A sister tweet reinforcement process for modeling hashtag popularity. INFOCOM 2017: 1-9 - [i4]Ali Zarezade, Abir De, Hamid R. Rabiee, Manuel Gomez-Rodriguez:
Cheshire: An Online Algorithm for Activity Maximization in Social Networks. CoRR abs/1703.02059 (2017) - [i3]Behzad Tabibian, Utkarsh Upadhyay, Abir De, Ali Zarezade, Bernhard Schölkopf, Manuel Gomez-Rodriguez:
Optimizing Human Learning. CoRR abs/1712.01856 (2017) - 2016
- [j1]Abir De, Sourangshu Bhattacharya, Sourav Sarkar, Niloy Ganguly, Soumen Chakrabarti:
Discriminative Link Prediction using Local, Community, and Global Signals. IEEE Trans. Knowl. Data Eng. 28(8): 2057-2070 (2016) - [c6]Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, Manuel Gomez-Rodriguez:
Learning and Forecasting Opinion Dynamics in Social Networks. NIPS 2016: 397-405 - 2015
- [c5]Niket Tandon, Gerard de Melo, Abir De, Gerhard Weikum:
Knowlywood: Mining Activity Knowledge From Hollywood Narratives. CIKM 2015: 223-232 - [c4]Niket Tandon, Gerhard Weikum, Gerard de Melo, Abir De:
Lights, Camera, Action: Knowledge Extraction from Movie Scripts. WWW (Companion Volume) 2015: 127-128 - [i2]Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, Manuel Gomez-Rodriguez:
Modeling Opinion Dynamics in Diffusion Networks. CoRR abs/1506.05474 (2015) - 2014
- [c3]Abir De, Sourangshu Bhattacharya, Parantapa Bhattacharya, Niloy Ganguly, Soumen Chakrabarti:
Learning a Linear Influence Model from Transient Opinion Dynamics. CIKM 2014: 401-410 - 2013
- [c2]Abir De, Niloy Ganguly, Soumen Chakrabarti:
Discriminative Link Prediction Using Local Links, Node Features and Community Structure. ICDM 2013: 1009-1018 - [i1]Abir De, Niloy Ganguly, Soumen Chakrabarti:
Discriminative Link Prediction using Local Links, Node Features and Community Structure. CoRR abs/1310.4579 (2013) - 2012
- [c1]Abir De, Maunendra Sankar Desarkar, Niloy Ganguly, Pabitra Mitra:
Local learning of item dissimilarity using content and link structure. RecSys 2012: 221-224
Coauthor Index
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last updated on 2024-10-21 20:29 CEST by the dblp team
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