Kolar, Mladen

51 publications

CPAL 2025 Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar

JMLR 2025 Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback Boxin Zhao, Lingxiao Wang, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Chaochao Chen, Mladen Kolar

AISTATS 2025 High-Dimensional Differential Parameter Inference in Exponential Family Using Time Score Matching Daniel James Williams, Leyang Wang, Qizhen Ying, Song Liu, Mladen Kolar

AISTATS 2024 Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models Zhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam

JMLR 2024 Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning Luofeng Liao, Zuyue Fu, Zhuoran Yang, Yixin Wang, Dingli Ma, Mladen Kolar, Zhaoran Wang

MLJ 2024 Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Optimization Luofeng Liao, Li Shen, Jia Duan, Mladen Kolar, Dacheng Tao

CLeaR 2024 On the Lasso for Graphical Continuous Lyapunov Models Philipp Dettling, Mathias Drton, Mladen Kolar

ICML 2024 Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang

ICML 2023 Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez, Mladen Kolar

ICML 2023 Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar

AISTATS 2023 Differentially Private Matrix Completion Through Low-Rank Matrix Factorization Lingxiao Wang, Boxin Zhao, Mladen Kolar

AAAI 2023 Gradient-Variation Bound for Online Convex Optimization with Constraints Shuang Qiu, Xiaohan Wei, Mladen Kolar

TMLR 2023 L-SVRG and L-Katyusha with Adaptive Sampling Boxin Zhao, Boxiang Lyu, Mladen Kolar

AISTATS 2023 One Policy Is Enough: Parallel Exploration with a Single Policy Is Near-Optimal for Reward-Free Reinforcement Learning Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar

TMLR 2023 Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques Filip Hanzely, Boxin Zhao, Mladen Kolar

JMLR 2022 A Nonconvex Framework for Structured Dynamic Covariance Recovery Katherine Tsai, Mladen Kolar, Oluwasanmi Koyejo

NeurIPSW 2022 Adaptive Inexact Sequential Quadratic Programming via Iterative Randomized Sketching Ilgee Hong, Sen Na, Mladen Kolar

JMLR 2022 FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting Boxin Zhao, Y. Samuel Wang, Mladen Kolar

ICML 2022 Pessimism Meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang

ICML 2021 Robust Inference for High-Dimensional Linear Models via Residual Randomization Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar

JMLR 2020 Estimation of a Low-Rank Topic-Based Model for Information Cascades Ming Yu, Varun Gupta, Mladen Kolar

NeurIPS 2020 Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang

ICML 2020 Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar

JMLR 2020 Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching Ming Yu, Varun Gupta, Mladen Kolar

NeurIPS 2019 Convergent Policy Optimization for Safe Reinforcement Learning Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang

NeurIPS 2019 Direct Estimation of Differential Functional Graphical Models Boxin Zhao, Y. Samuel Wang, Mladen Kolar

JMLR 2019 High-Dimensional Varying Index Coefficient Models via Stein's Identity Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar

UAI 2019 Joint Nonparametric Precision Matrix Estimation with Confounding Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo

AISTATS 2019 Learning Influence-Receptivity Network Structure with Guarantee Ming Yu, Varun Gupta, Mladen Kolar

ICML 2019 Partially Linear Additive Gaussian Graphical Models Sinong Geng, Minhao Yan, Mladen Kolar, Sanmi Koyejo

NeurIPS 2018 Provable Gaussian Embedding with One Observation Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang

ICML 2017 Efficient Distributed Learning with Sparsity Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang

AISTATS 2017 Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-Dimensional Data Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nati Srebro

NeurIPS 2017 The Expxorcist: Nonparametric Graphical Models via Conditional Exponential Densities Arun Suggala, Mladen Kolar, Pradeep K Ravikumar

AISTATS 2016 Distributed Multi-Task Learning Jialei Wang, Mladen Kolar, Nathan Srebro

AISTATS 2016 Inference for High-Dimensional Exponential Family Graphical Models Jialei Wang, Mladen Kolar

NeurIPS 2016 Statistical Inference for Pairwise Graphical Models Using Score Matching Ming Yu, Mladen Kolar, Varun Gupta

NeurIPS 2015 Learning Structured Densities via Infinite Dimensional Exponential Families Siqi Sun, Mladen Kolar, Jinbo Xu

JMLR 2014 Graph Estimation from Multi-Attribute Data Mladen Kolar, Han Liu, Eric P. Xing

ICML 2013 Feature Selection in High-Dimensional Classification Mladen Kolar, Han Liu

ICML 2013 Markov Network Estimation from Multi-Attribute Data Mladen Kolar, Han Liu, Eric Xing

ICML 2012 Consistent Covariance Selection from Data with Missing Values Mladen Kolar, Eric P. Xing

AISTATS 2012 Marginal Regression for Multitask Learning Mladen Kolar, Han Liu

ICML 2012 Variance Function Estimation in High-Dimensions Mladen Kolar, James Sharpnack

NeurIPS 2011 Minimax Localization of Structural Information in Large Noisy Matrices Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh

AISTATS 2011 On Time Varying Undirected Graphs Mladen Kolar, Eric P. Xing

JMLR 2011 Union Support Recovery in Multi-Task Learning Mladen Kolar, John Lafferty, Larry Wasserman

ICML 2010 On Sparse Nonparametric Conditional Covariance Selection Mladen Kolar, Ankur P. Parikh, Eric P. Xing

AISTATS 2010 Ultra-High Dimensional Multiple Output Learning with Simultaneous Orthogonal Matching Pursuit: Screening Approach Mladen Kolar, Eric Xing

NeurIPS 2009 Sparsistent Learning of Varying-Coefficient Models with Structural Changes Mladen Kolar, Le Song, Eric P. Xing

NeurIPS 2009 Time-Varying Dynamic Bayesian Networks Le Song, Mladen Kolar, Eric P. Xing