Mladen Kolar - RankMe

118 papers A* 17A 12Journal 77Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism. CPAL Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2025	J	`jnl`	Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback. J. Mach. Learn. Res. Boxin Zhao, Lingxiao Wang, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Chaochao Chen, Mladen Kolar
2025	A	`conf`	High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching. AISTATS Daniel J. Williams, Leyang Wang, Qizhen Ying, Song Liu, Mladen Kolar
2025	J	`jnl`	High-Dimensional Markov-switching Ordinary Differential Processes. CoRR Katherine Tsai, Mladen Kolar, Sanmi Koyejo
2025	J	`jnl`	Provable Accelerated Bayesian Optimization with Knowledge Transfer. CoRR Haitao Lin, Boxin Zhao, Mladen Kolar, Chong Liu
2024	J	`jnl`	A Fast Temporal Decomposition Procedure for Long-Horizon Nonlinear Dynamic Programming. Math. Oper. Res. Sen Na, Mihai Anitescu, Mladen Kolar
2024	J	`jnl`	AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods. CoRR Tim Tsz-Kit Lau, Han Liu, Mladen Kolar
2024	J	`jnl`	Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism. CoRR Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2024	J	`jnl`	Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods. CoRR Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
2024	J	`jnl`	Convergence Analysis of Accelerated Stochastic Gradient Descent Under the Growth Condition. Math. Oper. Res. You-Lin Chen, Sen Na, Mladen Kolar
2024	J	`jnl`	Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems. SIAM J. Optim. Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar
2024	J	`jnl`	High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching. CoRR Daniel J. Williams, Leyang Wang, Qizhen Ying, Song Liu, Mladen Kolar
2024	A	`conf`	Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models. AISTATS Zhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam
2024	J	`jnl`	Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning. J. Mach. Learn. Res. Luofeng Liao, Zuyue Fu, Zhuoran Yang, Yixin Wang, Dingli Ma, Mladen Kolar, Zhaoran Wang
2024	J	`jnl`	Local AdaGrad-type algorithm for stochastic convex-concave optimization. Mach. Learn. Luofeng Liao, Li Shen, Jia Duan, Mladen Kolar, Dacheng Tao
2024	—	`conf`	On the Lasso for Graphical Continuous Lyapunov Models. CLeaR Philipp Dettling, Mathias Drton, Mladen Kolar
2024	J	`jnl`	Personalized Binomial DAGs Learning with Network Structured Covariates. CoRR Boxin Zhao, Weishi Wang, Dingyuan Zhu, Ziqi Liu, Dong Wang, Zhiqiang Zhang, Jun Zhou, Mladen Kolar
2024	A*	`conf`	Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. ICML Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang
2024	J	`jnl`	Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. CoRR Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang
2024	J	`jnl`	Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimation. CoRR Boxin Zhao, Cong Ma, Mladen Kolar
2024	J	`jnl`	Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models. CoRR Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar
2023	A*	`conf`	Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm. ICML Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez, Mladen Kolar
2023	J	`jnl`	Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm. CoRR Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez, Mladen Kolar
2023	J	`jnl`	An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians. Math. Program. Sen Na, Mihai Anitescu, Mladen Kolar
2023	A*	`conf`	Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching. ICML Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar
2023	J	`jnl`	Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching. CoRR Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar
2023	A	`conf`	Differentially Private Matrix Completion through Low-rank Matrix Factorization. AISTATS Lingxiao Wang, Boxin Zhao, Mladen Kolar
2023	A*	`conf`	Gradient-Variation Bound for Online Convex Optimization with Constraints. AAAI Shuang Qiu, Xiaohan Wei, Mladen Kolar
2023	J	`jnl`	Inconsistency of cross-validation for structure learning in Gaussian graphical models. CoRR Zhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam
2023	J	`jnl`	Inequality constrained stochastic nonlinear optimization via active-set sequential quadratic programming. Math. Program. Sen Na, Mihai Anitescu, Mladen Kolar
2023	J	`jnl`	L-SVRG and L-Katyusha with Adaptive Sampling. Trans. Mach. Learn. Res. Boxin Zhao, Boxiang Lyu, Mladen Kolar
2023	A	`conf`	One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning. AISTATS Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar
2023	J	`jnl`	Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques. Trans. Mach. Learn. Res. Filip Hanzely, Boxin Zhao, Mladen Kolar
2022	J	`jnl`	A Nonconvex Framework for Structured Dynamic Covariance Recovery. J. Mach. Learn. Res. Katherine Tsai, Mladen Kolar, Oluwasanmi Koyejo
2022	—	`conf`	Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems. SIGMETRICS (Abstracts) Yuwei Luo, Varun Gupta, Mladen Kolar
2022	J	`jnl`	Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems. Proc. ACM Meas. Anal. Comput. Syst. Yuwei Luo, Varun Gupta, Mladen Kolar
2022	J	`jnl`	FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting. J. Mach. Learn. Res. Boxin Zhao, Y. Samuel Wang, Mladen Kolar
2022	J	`jnl`	L-SVRG and L-Katyusha with Adaptive Sampling. CoRR Boxin Zhao, Boxiang Lyu, Mladen Kolar
2022	J	`jnl`	Latent Multimodal Functional Graphical Model Estimation. CoRR Katherine Tsai, Boxin Zhao, Oluwasanmi Koyejo, Mladen Kolar
2022	J	`jnl`	One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning. CoRR Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar
2022	J	`jnl`	Personalized Federated Learning with Multiple Known Clusters. CoRR Boxiang Lyu, Filip Hanzely, Mladen Kolar
2022	A*	`conf`	Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. ICML Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang
2022	J	`jnl`	Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. CoRR Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang
2021	J	`jnl`	Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback. CoRR Boxin Zhao, Ziqi Liu, Chaochao Chen, Mladen Kolar, Zhiqiang Zhang, Jun Zhou
2021	J	`jnl`	An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians. CoRR Sen Na, Mihai Anitescu, Mladen Kolar
2021	J	`jnl`	Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems. CoRR Yuwei Luo, Varun Gupta, Mladen Kolar
2021	J	`jnl`	High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection Approach. CoRR Boxin Zhao, Shengjun Zhai, Y. Samuel Wang, Mladen Kolar
2021	J	`jnl`	Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming. CoRR Sen Na, Mihai Anitescu, Mladen Kolar
2021	J	`jnl`	Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning. CoRR Luofeng Liao, Zuyue Fu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang
2021	J	`jnl`	Joint Gaussian Graphical Model Estimation: A Survey. CoRR Katherine Tsai, Oluwasanmi Koyejo, Mladen Kolar
2021	J	`jnl`	Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Minimax Problems. CoRR Luofeng Liao, Li Shen, Jia Duan, Mladen Kolar, Dacheng Tao
2021	J	`jnl`	Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques. CoRR Filip Hanzely, Boxin Zhao, Mladen Kolar
2021	A*	`conf`	Robust Inference for High-Dimensional Linear Models via Residual Randomization. ICML Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar
2021	J	`jnl`	Tensor Canonical Correlation Analysis With Convergence and Statistical Guarantees. J. Comput. Graph. Stat. You-Lin Chen, Mladen Kolar, Ruey S. Tsay
2020	J	`jnl`	A Nonconvex Framework for Structured Dynamic Covariance Recovery. CoRR Katherine Tsai, Mladen Kolar, Oluwasanmi Koyejo
2020	J	`jnl`	Estimation of a Low-rank Topic-Based Model for Information Cascades. J. Mach. Learn. Res. Ming Yu, Varun Gupta, Mladen Kolar
2020	J	`jnl`	FuDGE: Functional Differential Graph Estimation with fully and discretely observed curves. CoRR Boxin Zhao, Y. Samuel Wang, Mladen Kolar
2020	J	`jnl`	Posterior Ratio Estimation for Latent Variables. CoRR Yulong Zhang, Mingxuan Yi, Song Liu, Mladen Kolar
2020	J	`jnl`	Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach. CoRR Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Zhaoran Wang, Mladen Kolar
2020	A*	`conf`	Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach. NeurIPS Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang
2020	J	`jnl`	Provably Training Neural Network Classifiers under Fairness Constraints. CoRR You-Lin Chen, Zhaoran Wang, Mladen Kolar
2020	A*	`conf`	Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. ICML Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
2020	J	`jnl`	Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. CoRR Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
2020	J	`jnl`	Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching. J. Mach. Learn. Res. Ming Yu, Varun Gupta, Mladen Kolar
2020	J	`jnl`	Statistical Inference for Networks of High-Dimensional Point Processes. CoRR Xu Wang, Mladen Kolar, Ali Shojaie
2019	A*	`conf`	Convergent Policy Optimization for Safe Reinforcement Learning. NeurIPS Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang
2019	J	`jnl`	Convergent Policy Optimization for Safe Reinforcement Learning. CoRR Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang
2019	A*	`conf`	Direct Estimation of Differential Functional Graphical Models. NeurIPS Boxin Zhao, Y. Samuel Wang, Mladen Kolar
2019	J	`jnl`	Direct Estimation of Differential Functional Graphical Models. CoRR Boxin Zhao, Y. Samuel Wang, Mladen Kolar
2019	J	`jnl`	High-dimensional Varying Index Coefficient Models via Stein's Identity. J. Mach. Learn. Res. Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
2019	A	`conf`	Joint Nonparametric Precision Matrix Estimation with Confounding. UAI Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo
2019	A	`conf`	Learning Influence-Receptivity Network Structure with Guarantee. AISTATS Ming Yu, Varun Gupta, Mladen Kolar
2019	J	`jnl`	Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator. CoRR Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
2019	A*	`conf`	Partially Linear Additive Gaussian Graphical Models. ICML Sinong Geng, Minhao Yan, Mladen Kolar, Sanmi Koyejo
2019	J	`jnl`	Partially Linear Additive Gaussian Graphical Models. CoRR Sinong Geng, Minhao Yan, Mladen Kolar, Oluwasanmi Koyejo
2019	J	`jnl`	Tensor Canonical Correlation Analysis. CoRR You-Lin Chen, Mladen Kolar, Ruey S. Tsay
2018	J	`jnl`	Distributed Stochastic Multi-Task Learning with Graph Regularization. CoRR Weiran Wang, Jialei Wang, Mladen Kolar, Nathan Srebro
2018	J	`jnl`	High-dimensional Index Volatility Models via Stein's Identity. CoRR Sen Na, Mladen Kolar
2018	J	`jnl`	High-dimensional Varying Index Coefficient Models via Stein's Identity. CoRR Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
2018	J	`jnl`	Joint Nonparametric Precision Matrix Estimation with Confounding. CoRR Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo
2018	J	`jnl`	Learning Influence-Receptivity Network Structure with Guarantee. CoRR Ming Yu, Varun Gupta, Mladen Kolar
2018	A*	`conf`	Provable Gaussian Embedding with One Observation. NeurIPS Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang
2018	J	`jnl`	Provable Gaussian Embedding with One Observation. CoRR Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang
2017	A*	`conf`	An Influence-Receptivity Model for Topic Based Information Cascades. ICDM Ming Yu, Varun Gupta, Mladen Kolar
2017	J	`jnl`	An Influence-Receptivity Model for Topic based Information Cascades. CoRR Ming Yu, Varun Gupta, Mladen Kolar
2017	A*	`conf`	Efficient Distributed Learning with Sparsity. ICML Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang
2017	J	`jnl`	Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models. J. Mach. Learn. Res. Junwei Lu, Mladen Kolar, Han Liu
2017	A	`conf`	Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data. AISTATS Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nati Srebro
2017	—	`conf`	The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities. NIPS Arun Sai Suggala, Mladen Kolar, Pradeep Ravikumar
2016	J	`jnl`	Distributed Multi-Task Learning with Shared Representation. CoRR Jialei Wang, Mladen Kolar, Nathan Srebro
2016	A	`conf`	Distributed Multi-Task Learning. AISTATS Jialei Wang, Mladen Kolar, Nathan Srebro
2016	J	`jnl`	Efficient Distributed Learning with Sparsity. CoRR Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang
2016	A	`conf`	Inference for High-dimensional Exponential Family Graphical Models. AISTATS Jialei Wang, Mladen Kolar
2016	J	`jnl`	Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data. CoRR Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nathan Srebro
2016	—	`conf`	Statistical Inference for Pairwise Graphical Models Using Score Matching. NIPS Ming Yu, Mladen Kolar, Varun Gupta
2015	J	`jnl`	Distributed Multitask Learning. CoRR Jialei Wang, Mladen Kolar, Nathan Srebro
2015	—	`conf`	Learning structured densities via infinite dimensional exponential families. NIPS Siqi Sun, Mladen Kolar, Jinbo Xu
2015	J	`jnl`	Optimal Feature Selection in High-Dimensional Discriminant Analysis. IEEE Trans. Inf. Theory Mladen Kolar, Han Liu
2015	J	`jnl`	ROCKET: Robust Confidence Intervals via Kendall's Tau for Transelliptical Graphical Models. CoRR Rina Foygel Barber, Mladen Kolar
2014	J	`jnl`	Graph estimation from multi-attribute data. J. Mach. Learn. Res. Mladen Kolar, Han Liu, Eric P. Xing
2013	J	`jnl`	Estimating Undirected Graphs Under Weak Assumptions. CoRR Larry A. Wasserman, Mladen Kolar, Alessandro Rinaldo
2013	—	`conf`	Feature Selection in High-Dimensional Classification. ICML (1) Mladen Kolar, Han Liu
2013	—	`conf`	Markov Network Estimation From Multi-attribute Data. ICML (3) Mladen Kolar, Han Liu, Eric P. Xing
2013	—	`—`	Uncovering Structure in High-Dimensions: Networks and Multi-task Learning Problems. Mladen Kolar
2012	A*	`conf`	Consistent Covariance Selection From Data With Missing Values. ICML Mladen Kolar, Eric P. Xing
2012	A	`conf`	Marginal Regression For Multitask Learning. AISTATS Mladen Kolar, Han Liu
2012	A*	`conf`	Variance Function Estimation in High-dimensions. ICML Mladen Kolar, James Sharpnack
2011	—	`conf`	Minimax Localization of Structural Information in Large Noisy Matrices. NIPS Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh
2011	A	`conf`	On Time Varying Undirected Graphs. AISTATS Mladen Kolar, Eric P. Xing
2011	J	`jnl`	Union Support Recovery in Multi-task Learning. J. Mach. Learn. Res. Mladen Kolar, John D. Lafferty, Larry A. Wasserman
2010	A*	`conf`	On Sparse Nonparametric Conditional Covariance Selection. ICML Mladen Kolar, Ankur P. Parikh, Eric P. Xing
2010	A	`conf`	Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach. AISTATS Mladen Kolar, Eric P. Xing
2009	J	`jnl`	KELLER: estimating time-varying interactions between genes. Bioinform. Le Song, Mladen Kolar, Eric P. Xing
2009	—	`conf`	Sparsistent Learning of Varying-coefficient Models with Structural Changes. NIPS Mladen Kolar, Le Song, Eric P. Xing
2009	—	`conf`	Time-Varying Dynamic Bayesian Networks. NIPS Le Song, Mladen Kolar, Eric P. Xing
2008	J	`jnl`	CSMET: Comparative Genomic Motif Detection via Multi-Resolution Phylogenetic Shadowing. PLoS Comput. Biol. Pradipta Ray, Suyash Shringarpure, Mladen Kolar, Eric P. Xing
2006	J	`jnl`	Comparison of Collocation Extraction Measures for Document Indexing. J. Comput. Inf. Technol. Sasa Petrovic, Jan Snajder, Bojana Dalbelo Basic, Mladen Kolar
2005	J	`jnl`	Computer-Aided Document Indexing System. J. Comput. Inf. Technol. Mladen Kolar, I. Vukmirovic, Bojana Dalbelo Basic, Jan Snajder