Tarokh, Vahid

43 publications

TMLR 2025 An Information-Theoretic Lower Bound on the Generalization Error of Autoencoders Shyam Venkatasubramanian, Sean Moushegian, Ahmed Aloui, Vahid Tarokh

UAI 2025 CATE Estimation with Potential Outcome Imputation from Local Regression Ahmed Aloui, Juncheng Dong, Cat Phuoc Le, Vahid Tarokh

UAI 2025 Conditional Average Treatment Effect Estimation Under Hidden Confounders Ahmed Aloui, Juncheng Dong, Ali Hasan, Vahid Tarokh

ICML 2025 Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization Junyi Liao, Zihan Zhu, Ethan X Fang, Zhuoran Yang, Vahid Tarokh

ICLR 2025 Elliptic Loss Regularization Ali Hasan, Haoming Yang, Yuting Ng, Vahid Tarokh

ICML 2025 In-Context Reinforcement Learning from Suboptimal Historical Data Juncheng Dong, Moyang Guo, Ethan X Fang, Zhuoran Yang, Vahid Tarokh

NeurIPS 2025 Learn2Mix: Training Neural Networks Using Adaptive Data Integration Shyam Venkatasubramanian, Vahid Tarokh

AISTATS 2025 Parabolic Continual Learning Haoming Yang, Ali Hasan, Vahid Tarokh

AISTATS 2025 Steinmetz Neural Networks for Complex-Valued Data Shyam Venkatasubramanian, Ali Pezeshki, Vahid Tarokh

TMLR 2025 Understanding and Robustifying Sub-Domain Alignment for Domain Adaptation Yiling Liu, Juncheng Dong, Ziyang Jiang, Ahmed Aloui, Keyu Li, Michael Hunter Klein, Vahid Tarokh, David Carlson

AISTATS 2025 Variational Adversarial Training Towards Policies with Improved Robustness Juncheng Dong, Hao-Lun Hsu, Qitong Gao, Vahid Tarokh, Miroslav Pajic

UAI 2024 Base Models for Parabolic Partial Differential Equations Xingzi Xu, Ali Hasan, Jie Ding, Vahid Tarokh

UAI 2024 Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions Patrick Kuiper, Ali Hasan, Wenhao Yang, Yuting Ng, Hoda Bidkhori, Jose Blanchet, Vahid Tarokh

ICMLW 2024 In-Context Reinforcement Learning Without Optimal Action Labels Juncheng Dong, Moyang Guo, Ethan X Fang, Zhuoran Yang, Vahid Tarokh

AISTATS 2024 Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes Haoming Yang, Ali Hasan, Yuting Ng, Vahid Tarokh

UAI 2024 Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks Shyam Venkatasubramanian, Ahmed Aloui, Vahid Tarokh

ICLR 2023 Characteristic Neural Ordinary Differential Equation Xingzi Xu, Ali Hasan, Khalil Elkhalil, Jie Ding, Vahid Tarokh

UAI 2023 Inference and Sampling of Point Processes from Diffusion Excursions Ali Hasan, Yu Chen, Yuting Ng, Mohamed Abdelghani, Anderson Schneider, Vahid Tarokh

NeurIPS 2023 Off-Policy Evaluation for Human Feedback Qitong Gao, Ge Gao, Juncheng Dong, Vahid Tarokh, Min Chi, Miroslav Pajic

ICML 2023 PASTA: Pessimistic Assortment Optimization Juncheng Dong, Weibin Mo, Zhengling Qi, Cong Shi, Ethan X Fang, Vahid Tarokh

ICLR 2023 Pruning Deep Neural Networks from a Sparsity Perspective Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh

NeurIPSW 2023 Representation Learning for Extremes Ali Hasan, Yuting Ng, Jose Blanchet, Vahid Tarokh

UAI 2023 Robust Quickest Change Detection for Unnormalized Models Suya Wu, Enmao Diao, Jie Ding, Taposh Banerjee, Vahid Tarokh

AISTATS 2023 Score-Based Quickest Change Detection for Unnormalized Models Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh

UAI 2023 Transfer Learning for Individual Treatment Effect Estimation Ahmed Aloui, Juncheng Dong, Cat P Le, Vahid Tarokh

ICLR 2022 Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan Malof, Mohammadreza Soltani, Willie Padilla, Vahid Tarokh

NeurIPS 2022 GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations Enmao Diao, Jie Ding, Vahid Tarokh

NeurIPS 2022 Inference and Sampling for Archimax Copulas Yuting Ng, Ali Hasan, Vahid Tarokh

UAI 2022 Modeling Extremes with $d$-Max-Decreasing Neural Networks Ali Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira, Sina Farsiu, Jose Blanchet, Vahid Tarokh

NeurIPS 2022 SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training Enmao Diao, Jie Ding, Vahid Tarokh

ICLR 2022 Task Affinity with Maximum Bipartite Matching in Few-Shot Learning Cat Phuoc Le, Juncheng Dong, Mohammadreza Soltani, Vahid Tarokh

AISTATS 2021 Fisher Auto-Encoders Khalil Elkhalil, Ali Hasan, Jie Ding, Sina Farsiu, Vahid Tarokh

UAI 2021 Generative Archimedean Copulas Yuting Ng, Ali Hasan, Khalil Elkhalil, Vahid Tarokh

ICLR 2021 HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao, Jie Ding, Vahid Tarokh

JMLR 2021 Model Linkage Selection for Cooperative Learning Jiaying Zhou, Jie Ding, Kean Ming Tan, Vahid Tarokh

ICLR 2021 Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows Chris Cannella, Mohammadreza Soltani, Vahid Tarokh

IJCAI 2020 Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh

NeurIPS 2019 Gradient Information for Representation and Modeling Jie Ding, Robert Calderbank, Vahid Tarokh

ICLR 2019 SGD Converges to Global Minimum in Deep Learning via Star-Convex Path Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh

NeurIPS 2019 SpiderBoost and Momentum: Faster Variance Reduction Algorithms Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh

NeurIPS 2018 Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels Shahin Shahrampour, Vahid Tarokh

AAAI 2018 On Data-Dependent Random Features for Improved Generalization in Supervised Learning Shahin Shahrampour, Ahmad Beirami, Vahid Tarokh

NeurIPS 2017 On Optimal Generalizability in Parametric Learning Ahmad Beirami, Meisam Razaviyayn, Shahin Shahrampour, Vahid Tarokh