Publications (87)
Convergent Policy Optimization for Safe Reinforcement Learning
Ming Yu, Zhuoran Yang, Mladen Kolar +1
Provable Accelerated Bayesian Optimization with Knowledge Transfer
Haitao Lin, Boxin Zhao, Mladen Kolar +1
High-dimensional Varying Index Coefficient Models via Stein's Identity
Sen Na, Zhuoran Yang, Zhaoran Wang +1
On the Lasso for Graphical Continuous Lyapunov Models
Philipp Dettling, Mathias Drton, Mladen Kolar
Muon with Nesterov Momentum: Heavy-Tailed Noise and (Randomized) Inexact Polar Decomposition
Sayantan Choudhury, Xiaoran Cheng, Martin TakÃ¡Ä +2
Latent Multimodal Functional Graphical Model Estimation
Katherine Tsai, Boxin Zhao, Sanmi Koyejo +1
Constrained High Dimensional Statistical Inference
Ming Yu, Varun Gupta, Mladen Kolar
SMART: A Spectral Transfer Approach to Multi-Task Learning
Boxin Zhao, Mladen Kolar, Jinchi Lv
ROCKET: Robust Confidence Intervals via Kendall's Tau for Transelliptical Graphical Models
Rina Foygel Barber, Mladen Kolar
Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: A Sure Screening Approach
Mladen Kolar, Eric P. Xing
Post-selection inference on high-dimensional varying-coefficient quantile regression model
Ran Dai, Mladen Kolar
A Nonconvex Framework for Structured Dynamic Covariance Recovery
Katherine Tsai, Mladen Kolar, Oluwasanmi Koyejo
Tensor Canonical Correlation Analysis with Convergence and Statistical Guarantees
You-Lin Chen, Mladen Kolar, Ruey S. Tsay
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm
Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez +1
Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching
Ming Yu, Varun Gupta, Mladen Kolar
FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting
Boxin Zhao, Y. Samuel Wang, Mladen Kolar
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang, Boxiang Lyu, Shuang Qiu +2
Efficient Distributed Learning with Sparsity
Jialei Wang, Mladen Kolar, Nathan Srebro +1
Gradient-Variation Bound for Online Convex Optimization with Constraints
Shuang Qiu, Xiaohan Wei, Mladen Kolar
Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimation
Boxin Zhao, Cong Ma, Mladen Kolar
An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
Sen Na, Mihai Anitescu, Mladen Kolar
Joint Gaussian Graphical Model Estimation: A Survey
Katherine Tsai, Oluwasanmi Koyejo, Mladen Kolar
Distributed Multi-Task Learning with Shared Representation
Jialei Wang, Mladen Kolar, Nathan Srebro
L-SVRG and L-Katyusha with Adaptive Sampling
Boxin Zhao, Boxiang Lyu, Mladen Kolar
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 +1
Robust Inference for High-Dimensional Linear Models via Residual Randomization
Y. Samuel Wang, Si Kai Lee, Panos Toulis +1
Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model
Junwei Lu, Mladen Kolar, Han Liu
High-Dimensional Markov-switching Ordinary Differential Processes
Katherine Tsai, Mladen Kolar, Sanmi Koyejo
Confidence Sets for Causal Orderings
Y. Samuel Wang, Mladen Kolar, Mathias Drton
Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters
Alexander Yukhimchuk, Mladen Kolar, Martin TakÃ¡Ä +1
Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach
Luofeng Liao, You-Lin Chen, Zhuoran Yang +3
Estimation of a Low-rank Topic-Based Model for Information Cascades
Ming Yu, Varun Gupta, Mladen Kolar
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Sen Na, Yuwei Luo, Zhuoran Yang +2
Provable Gaussian Embedding with One Observation
Ming Yu, Zhuoran Yang, Tuo Zhao +2
Graph Estimation From Multi-attribute Data
Mladen Kolar, Han Liu, Eric P. Xing
Estimating time-varying networks
Mladen Kolar, Le Song, Amr Ahmed +1
Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Optimization
Luofeng Liao, Li Shen, Jia Duan +2
Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Sen Na, Mladen Kolar, Oluwasanmi Koyejo
Inference for Sparse Conditional Precision Matrices
Jialei Wang, Mladen Kolar
Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems
Yuchen Fang, Sen Na, Michael W. Mahoney +1
Union Support Recovery in Multi-task Learning
Mladen Kolar, John Lafferty, Larry Wasserman
A General Framework for Robust Testing and Confidence Regions in High-Dimensional Quantile Regression
Tianqi Zhao, Mladen Kolar, Han Liu
Direct Estimation of Differential Functional Graphical Models
Boxin Zhao, Y. Samuel Wang, Mladen Kolar
Estimating Undirected Graphs Under Weak Assumptions
Larry Wasserman, Mladen Kolar, Alessandro Rinaldo
Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming
Sen Na, Mihai Anitescu, Mladen Kolar
Provably Training Overparameterized Neural Network Classifiers with Non-convex Constraints
You-Lin Chen, Zhaoran Wang, Mladen Kolar
Two-sample inference for high-dimensional Markov networks
Byol Kim, Song Liu, Mladen Kolar
Optimal variable selection in multi-group sparse discriminant analysis
Irina Gaynanova, Mladen Kolar
Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach
Ming Yu, Varun Gupta, Mladen Kolar
Privacy from Symmetry: Orthogonally Equivariant Transformers for LLM Inference
Alexander Yukhimchuk, Andrey Shulga, Mladen Kolar +1
A Fast Temporal Decomposition Procedure for Long-horizon Nonlinear Dynamic Programming
Sen Na, Mihai Anitescu, Mladen Kolar
Personalized Federated Learning with Multiple Known Clusters
Boxiang Lyu, Filip Hanzely, Mladen Kolar
Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism
Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu +2
Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
Yuchen Fang, Sen Na, Michael W. Mahoney +1
Partially Linear Additive Gaussian Graphical Models
Sinong Geng, Minhao Yan, Mladen Kolar +1
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data
Jialei Wang, Jason D. Lee, Mehrdad Mahdavi +2
Variance function estimation in high-dimensions
Mladen Kolar, James Sharpnack
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Boxin Zhao, Lingxiao Wang, Ziqi Liu +4
Simultaneous Inference for Covariance and Precision Matrices of Long-Range Dependent Time Series
Percy S. Zhai, Mladen Kolar, Wei Biao Wu
Joint Nonparametric Precision Matrix Estimation with Confounding
Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo
Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods
Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu +2
AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods
Tim Tsz-Kit Lau, Han Liu, Mladen Kolar
Distributed Stochastic Multi-Task Learning with Graph Regularization
Weiran Wang, Jialei Wang, Mladen Kolar +1
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
Daniel J. Williams, Leyang Wang, Qizhen Ying +2
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning
Boxiang Lyu, Zhaoran Wang, Mladen Kolar +1
Scalable Peaceman-Rachford Splitting Method with Proximal Terms
Sen Na, Mingyuan Ma, Mladen Kolar
Uniform Inference for High-dimensional Quantile Regression: Linear Functionals and Regression Rank Scores
Jelena Bradic, Mladen Kolar
Recovering Block-structured Activations Using Compressive Measurements
Sivaraman Balakrishnan, Mladen Kolar, Alessandro Rinaldo +1
Convergence Analysis of Accelerated Stochastic Gradient Descent under the Growth Condition
You-Lin Chen, Sen Na, Mladen Kolar
Estimating Networks With Jumps
Mladen Kolar, Eric P. Xing
Mean and variance estimation in high-dimensional heteroscedastic models with non-convex penalties
James Sharpnack, Mladen Kolar
Sparsistent Estimation of Time-Varying Discrete Markov Random Fields
Mladen Kolar, Eric P. Xing
Personalized Binomial DAGs Learning with Network Structured Covariates
Boxin Zhao, Weishi Wang, Dingyuan Zhu +5
Optimal Feature Selection in High-Dimensional Discriminant Analysis
Mladen Kolar, Han Liu
Posterior Ratio Estimation of Latent Variables
Song Liu, Yulong Zhang, Mingxuan Yi +1
Inconsistency of cross-validation for structure learning in Gaussian graphical models
Zhao Lyu, Wai Ming Tai, Mladen Kolar +1
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching
Ilgee Hong, Sen Na, Michael W. Mahoney +1
Learning Influence-Receptivity Network Structure with Guarantee
Ming Yu, Varun Gupta, Mladen Kolar
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques
Filip Hanzely, Boxin Zhao, Mladen Kolar
Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator
Yuwei Luo, Zhuoran Yang, Zhaoran Wang +1
High-dimensional Index Volatility Models via Stein's Identity
Sen Na, Mladen Kolar
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning
Luofeng Liao, Zuyue Fu, Zhuoran Yang +3
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models
Junwei Lu, Mladen Kolar, Han Liu
Distributed Multitask Learning
Jialei Wang, Mladen Kolar, Nathan Srebro
Statistical Inference for Networks of High-Dimensional Point Processes
Xu Wang, Mladen Kolar, Ali Shojaie
High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection Approach
Boxin Zhao, Percy S. Zhai, Y. Samuel Wang +1
Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems
Yuwei Luo, Varun Gupta, Mladen Kolar