← Authors

Mladen Kolar

44 papers · 2009–2025 · 7 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (16) πŸ—ΊοΈ Taxonomy Completionist (26) 🐝 Cross-Pollinator (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer πŸ”¬ Deep Specialist (14) πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (97) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ⚑ Prolific Year (6) πŸ’Ž Century Club (44) πŸ”₯ Unstoppable (17)

Conferences

AISTATS (11) ICML (10) JMLR (10) NIPS (10) AAAI (1) CLEAR (1) UAI (1)

Top co-authors

Zhuoran Yang (7) Zhaoran Wang (7) Ming Yu (6) Boxin Zhao (5) Han Liu (5) Jialei Wang (4) Varun Gupta (4) Eric P. Xing (4) Boxiang Lyu (4) Y. Samuel Wang (3)

Research topics

Statistics (1)

Keywords

graphical model (10) exponential family (5) variable selection (5) hypothesis testing (4) graph estimation (4) probabilistic graphical model (3) statistical inference (3) feature selection (3) causal inference (3) confidence interval (3) score matching (3) distributed learning (2) sparse estimation (2) multi-task learning (2) brain connectivity (2) time series analysis (2) high-dimensional inference (2) constrained optimization (2) structure learning (2) nonconvex optimization (2)

Papers

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback JMLR 2025
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching AISTATS 2025
Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models AISTATS 2024
On the Lasso for Graphical Continuous Lyapunov Models CLEAR 2024
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning ICML 2024
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning JMLR 2024
Differentially Private Matrix Completion through Low-rank Matrix Factorization AISTATS 2023
Gradient-Variation Bound for Online Convex Optimization with Constraints AAAI 2023
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm ICML 2023
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching ICML 2023
One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning AISTATS 2023
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning ICML 2022
FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting JMLR 2022
A Nonconvex Framework for Structured Dynamic Covariance Recovery JMLR 2022
Robust Inference for High-Dimensional Linear Models via Residual Randomization ICML 2021
Estimation of a Low-rank Topic-Based Model for Information Cascades JMLR 2020
Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching JMLR 2020
Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach NIPS 2020
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees ICML 2020
Joint Nonparametric Precision Matrix Estimation with Confounding UAI 2019
Direct Estimation of Differential Functional Graphical Models NIPS 2019
Convergent Policy Optimization for Safe Reinforcement Learning NIPS 2019
Learning Influence-Receptivity Network Structure with Guarantee AISTATS 2019
Partially Linear Additive Gaussian Graphical Models ICML 2019
High-dimensional Varying Index Coefficient Models via Stein's Identity JMLR 2019
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models JMLR 2018
Provable Gaussian Embedding with One Observation NIPS 2018
Efficient Distributed Learning with Sparsity ICML 2017
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data AISTATS 2017
The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities NIPS 2017
Statistical Inference for Pairwise Graphical Models Using Score Matching NIPS 2016
Inference for High-dimensional Exponential Family Graphical Models AISTATS 2016
Distributed Multi-Task Learning AISTATS 2016
Learning structured densities via infinite dimensional exponential families NIPS 2015
Graph Estimation From Multi-Attribute Data JMLR 2014
Feature Selection in High-Dimensional Classification ICML 2013
Markov Network Estimation From Multi-attribute Data ICML 2013
Marginal Regression For Multitask Learning AISTATS 2012
On Time Varying Undirected Graphs AISTATS 2011
Union Support Recovery in Multi-task Learning JMLR 2011
Minimax Localization of Structural Information in Large Noisy Matrices NIPS 2011
Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach AISTATS 2010
Time-Varying Dynamic Bayesian Networks NIPS 2009
Sparsistent Learning of Varying-coefficient Models with Structural Changes NIPS 2009