Klabjan, Diego

23 publications

UAI 2025 A Mirror Descent Perspective of Smoothed Sign Descent Shuyang Wang, Diego Klabjan

AISTATS 2025 Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score Minimization Ziwei Su, Diego Klabjan

NeurIPS 2025 Investigating Hallucinations of Time Series Foundation Models Through Signal Subspace Analysis Yufeng Zou, Zijian Wang, Diego Klabjan, Han Liu

AISTATS 2025 Multi-Agent Multi-Armed Bandit Regret Complexity and Optimality Mengfan Xu, Diego Klabjan

NeurIPS 2025 Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions Siqiao Mu, Diego Klabjan

NeurIPS 2025 Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context Taejong Joo, Diego Klabjan

AAAI 2024 A Primal-Dual Algorithm for Hybrid Federated Learning Tom Overman, Garrett Blum, Diego Klabjan

ICML 2024 IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation Taejong Joo, Diego Klabjan

NeurIPS 2024 Improving Self-Training Under Distribution Shifts via Anchored Confidence with Theoretical Guarantees Taejong Joo, Diego Klabjan

ICML 2024 On the Second-Order Convergence of Biased Policy Gradient Algorithms Siqiao Mu, Diego Klabjan

NeurIPS 2023 Decentralized Randomly Distributed Multi-Agent Multi-Armed Bandit with Heterogeneous Rewards Mengfan Xu, Diego Klabjan

ICML 2023 Pareto Regret Analyses in Multi-Objective Multi-Armed Bandit Mengfan Xu, Diego Klabjan

JMLR 2023 Scale Invariant Power Iteration Cheolmin Kim, Youngseok Kim, Diego Klabjan

ICML 2021 A Probabilistic Approach to Neural Network Pruning Xin Qian, Diego Klabjan

IJCAI 2021 K-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks Yiming Xu, Diego Klabjan

AAAI 2021 Open-Set Recognition with Gaussian Mixture Variational Autoencoders Alexander Cao, Yuan Luo, Diego Klabjan

AISTATS 2020 Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes Cheolmin Kim, Diego Klabjan

ICML 2018 Competitive Multi-Agent Inverse Reinforcement Learning with Sub-Optimal Demonstrations Xingyu Wang, Diego Klabjan

JMLR 2017 Bayesian Network Learning via Topological Order Young Woong Park, Diego Klabjan

NeurIPS 2017 Improving the Expected Improvement Algorithm Chao Qin, Diego Klabjan, Daniel Russo

AAAI 2017 Regularization for Unsupervised Deep Neural Nets Baiyang Wang, Diego Klabjan

MLJ 2016 An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning Young Woong Park, Diego Klabjan

AAAI 2016 Temporal Topic Analysis with Endogenous and Exogenous Processes Baiyang Wang, Diego Klabjan