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2020 – today
- 2024
[c26]Li Du, Holden Lee, Jason Eisner, Ryan Cotterell:
When is a Language Process a Language Model? ACL (Findings) 2024: 11083-11094- [c25]Holden Lee:
Parallelising Glauber Dynamics. APPROX/RANDOM 2024: 49:1-49:24 - [c24]Muthu Chidambaram, Holden Lee, Colin McSwiggen, Semon Rezchikov:
How Flawed Is ECE? An Analysis via Logit Smoothing. ICML 2024 - [c23]Li Du, Afra Amini, Lucas Torroba Hennigen, Xinyan Velocity Yu, Holden Lee, Jason Eisner, Ryan Cotterell:
Principled Gradient-Based MCMC for Conditional Sampling of Text. ICML 2024 - [i31]Evan Camrud, Ewan Davies, Alex Karduna, Holden Lee:
Sampling List Packings. CoRR abs/2402.03520 (2024) - [i30]Muthu Chidambaram, Holden Lee, Colin McSwiggen, Semon Rezchikov:
How Flawed is ECE? An Analysis via Logit Smoothing. CoRR abs/2402.10046 (2024) - [i29]Khashayar Gatmiry, Jonathan A. Kelner, Holden Lee:
Learning Mixtures of Gaussians Using Diffusion Models. CoRR abs/2404.18869 (2024) - [i28]Holden Lee, Matheau Santana-Gijzen:
Convergence Bounds for Sequential Monte Carlo on Multimodal Distributions using Soft Decomposition. CoRR abs/2405.19553 (2024) - [i27]Holden Lee, Qiang Wu:
Sampling from the Continuous Random Energy Model in Total Variation Distance. CoRR abs/2407.00868 (2024) - [i26]Muthu Chidambaram, Khashayar Gatmiry, Sitan Chen, Holden Lee, Jianfeng Lu:
What does guidance do? A fine-grained analysis in a simple setting. CoRR abs/2409.13074 (2024) - 2023
- [j2]Tyler Helmuth
, Holden Lee, Will Perkins, Mohan Ravichandran, Qiang Wu:
Approximation Algorithms for the Random Field Ising Model. SIAM J. Discret. Math. 37(3): 1610-1629 (2023) - [c22]Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu:
Fisher information lower bounds for sampling. ALT 2023: 375-410 - [c21]Holden Lee, Jianfeng Lu, Yixin Tan:
Convergence of score-based generative modeling for general data distributions. ALT 2023: 946-985 - [c20]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Pitfalls of Gaussians as a noise distribution in NCE. ICLR 2023 - [c19]Hongrui Chen, Holden Lee, Jianfeng Lu:
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions. ICML 2023: 4735-4763 - [c18]Chenwei Wu, Holden Lee, Rong Ge:
Connecting Pre-trained Language Model and Downstream Task via Properties of Representation. NeurIPS 2023 - [c17]Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim:
The probability flow ODE is provably fast. NeurIPS 2023 - [c16]Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski:
Provable benefits of score matching. NeurIPS 2023 - [i25]Holden Lee, Zeyu Shen:
Improved Bound for Mixing Time of Parallel Tempering. CoRR abs/2304.01303 (2023) - [i24]Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim:
The probability flow ODE is provably fast. CoRR abs/2305.11798 (2023) - [i23]Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski:
Provable benefits of score matching. CoRR abs/2306.01993 (2023) - [i22]Holden Lee:
Parallelising Glauber dynamics. CoRR abs/2307.07131 (2023) - [i21]Li Du, Afra Amini, Lucas Torroba Hennigen, Xinyan Velocity Yu, Jason Eisner, Holden Lee, Ryan Cotterell:
Principled Gradient-based Markov Chain Monte Carlo for Text Generation. CoRR abs/2312.17710 (2023) - 2022
- [c15]Holden Lee:
Improved rates for prediction and identification of partially observed linear dynamical systems. ALT 2022: 668-698 - [c14]Frederic Koehler, Holden Lee, Andrej Risteski:
Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods. COLT 2022: 4945-4988 - [c13]Abraham Frandsen, Rong Ge, Holden Lee:
Extracting Latent State Representations with Linear Dynamics from Rich Observations. ICML 2022: 6705-6725 - [c12]Holden Lee, Jianfeng Lu, Yixin Tan:
Convergence for score-based generative modeling with polynomial complexity. NeurIPS 2022 - [i20]Frederic Koehler, Holden Lee, Andrej Risteski:
Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods. CoRR abs/2202.08907 (2022) - [i19]Holden Lee, Jianfeng Lu, Yixin Tan:
Convergence for score-based generative modeling with polynomial complexity. CoRR abs/2206.06227 (2022) - [i18]Holden Lee, Jianfeng Lu, Yixin Tan:
Convergence of score-based generative modeling for general data distributions. CoRR abs/2209.12381 (2022) - [i17]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Pitfalls of Gaussians as a noise distribution in NCE. CoRR abs/2210.00189 (2022) - [i16]Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu:
Fisher information lower bounds for sampling. CoRR abs/2210.02482 (2022) - [i15]Hongrui Chen, Holden Lee, Jianfeng Lu:
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions. CoRR abs/2211.01916 (2022) - 2021
- [c11]Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski:
Efficient sampling from the Bingham distribution. ALT 2021: 673-685 - [c10]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Universal Approximation Using Well-Conditioned Normalizing Flows. NeurIPS 2021: 12700-12711 - [i14]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flows. CoRR abs/2107.02951 (2021) - [i13]Tyler Helmuth, Holden Lee, Will Perkins, Mohan Ravichandran, Qiang Wu:
Approximation algorithms for the random-field Ising model. CoRR abs/2108.11889 (2021) - 2020
- [c9]Holden Lee, Cyril Zhang:
Robust guarantees for learning an autoregressive filter. ALT 2020: 490-517 - [c8]Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
No-Regret Prediction in Marginally Stable Systems. COLT 2020: 1714-1757 - [c7]Rong Ge, Holden Lee, Jianfeng Lu:
Estimating normalizing constants for log-concave distributions: algorithms and lower bounds. STOC 2020: 579-586 - [i12]Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
No-Regret Prediction in Marginally Stable Systems. CoRR abs/2002.02064 (2020) - [i11]Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski:
Efficient sampling from the Bingham distribution. CoRR abs/2010.00137 (2020) - [i10]Holden Lee:
Improved rates for identification of partially observed linear dynamical systems. CoRR abs/2011.10006 (2020)
2010 – 2019
- 2019
- [b1]Holden Lee:
MCMC algorithms for sampling from multimodal and changing distributions. Princeton University, USA, 2019 - [c6]Holden Lee, Oren Mangoubi, Nisheeth K. Vishnoi:
Online sampling from log-concave distributions. NeurIPS 2019: 1226-1237 - [c5]Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Rong Ge, Sanjeev Arora:
Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. NeurIPS 2019: 14574-14583 - [i9]Holden Lee, Oren Mangoubi, Nisheeth K. Vishnoi:
Online Sampling from Log-Concave Distributions. CoRR abs/1902.08179 (2019) - [i8]Holden Lee, Cyril Zhang:
Robust guarantees for learning an autoregressive filter. CoRR abs/1905.09897 (2019) - [i7]Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Sanjeev Arora, Rong Ge:
Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets. CoRR abs/1906.06247 (2019) - [i6]Rong Ge, Holden Lee, Jianfeng Lu:
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds. CoRR abs/1911.03043 (2019) - 2018
- [c4]Sanjeev Arora, Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Towards Provable Control for Unknown Linear Dynamical Systems. ICLR (Workshop) 2018 - [c3]Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Spectral Filtering for General Linear Dynamical Systems. NeurIPS 2018: 4639-4648 - [c2]Holden Lee, Andrej Risteski, Rong Ge:
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo. NeurIPS 2018: 7858-7867 - [i5]Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Spectral Filtering for General Linear Dynamical Systems. CoRR abs/1802.03981 (2018) - [i4]Rong Ge, Holden Lee, Andrej Risteski:
Simulated Tempering Langevin Monte Carlo II: An Improved Proof using Soft Markov Chain Decomposition. CoRR abs/1812.00793 (2018) - 2017
- [c1]Holden Lee, Rong Ge, Tengyu Ma, Andrej Risteski, Sanjeev Arora:
On the Ability of Neural Nets to Express Distributions. COLT 2017: 1271-1296 - [i3]Holden Lee, Rong Ge, Andrej Risteski, Tengyu Ma, Sanjeev Arora:
On the ability of neural nets to express distributions. CoRR abs/1702.07028 (2017) - [i2]Rong Ge, Holden Lee, Andrej Risteski:
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo. CoRR abs/1710.02736 (2017) - 2015
- [i1]Holden Lee:
Quadratic polynomials of small modulus cannot represent OR. CoRR abs/1509.08896 (2015) - 2014
- [j1]Holden Lee:
Vector Spaces. Arch. Formal Proofs 2014 (2014)
Coauthor Index
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last updated on 2024-10-21 20:30 CEST by the dblp team
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