← Authors

Vahid Tarokh

37 papers · 2017–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (8) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🧬 Topic Evolution 🀝 Dynamic Duo (12) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (103) ⚑ Prolific Year (6) πŸ“ˆ Trend Setter πŸ’Ž Century Club (37) πŸ”₯ Unstoppable (9)

Conferences

UAI (10) ICLR (8) NIPS (8) AISTATS (6) ICML (3) IJCAI (1) JMLR (1)

Top co-authors

Ali Hasan (12) Jie Ding (11) Juncheng Dong (9) Yuting Ng (7) Enmao Diao (6) Ahmed Aloui (4) Khalil Elkhalil (4) Haoming Yang (3) Yi Zhou (3) Yingbin Liang (3)

Research topics

Probability (1)

Keywords

fisher divergence (4) generative model (3) neural network architecture (2) nonconvex optimization (2) kullback-leibler divergence (2) federated learning (2) multivariate distribution (2) momentum method (2) diffusion process (2) semi-supervised learning (1) change detection (1) transfer learning (1) knowledge distillation (1) convergence analysis (1) representation learning (1) probabilistic modeling (1) empirical risk minimization (1) causal inference (1) distributed optimization (1) decentralized optimization (1)

Papers

Steinmetz Neural Networks for Complex-Valued Data AISTATS 2025
Variational Adversarial Training Towards Policies with Improved Robustness AISTATS 2025
Conditional Average Treatment Effect Estimation Under Hidden Confounders UAI 2025
Elliptic Loss Regularization ICLR 2025
In-Context Reinforcement Learning From Suboptimal Historical Data ICML 2025
Parabolic Continual Learning AISTATS 2025
Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization ICML 2025
CATE Estimation With Potential Outcome Imputation From Local Regression UAI 2025
Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions UAI 2024
Base Models for Parabolic Partial Differential Equations UAI 2024
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes AISTATS 2024
Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks UAI 2024
Pruning Deep Neural Networks from a Sparsity Perspective ICLR 2023
PASTA: Pessimistic Assortment Optimization ICML 2023
Off-Policy Evaluation for Human Feedback NIPS 2023
Score-based Quickest Change Detection for Unnormalized Models AISTATS 2023
Robust Quickest Change Detection for Unnormalized Models UAI 2023
Inference and sampling of point processes from diffusion excursions UAI 2023
Transfer learning for individual treatment effect estimation UAI 2023
Characteristic Neural Ordinary Differential Equation ICLR 2023
Task Affinity with Maximum Bipartite Matching in Few-Shot Learning ICLR 2022
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations NIPS 2022
Inference and Sampling for Archimax Copulas NIPS 2022
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training NIPS 2022
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions ICLR 2022
Modeling extremes with $d$-max-decreasing neural networks UAI 2022
Model Linkage Selection for Cooperative Learning JMLR 2021
Generative Archimedean copulas UAI 2021
Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows ICLR 2021
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients ICLR 2021
Fisher Auto-Encoders AISTATS 2021
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization IJCAI 2020
SpiderBoost and Momentum: Faster Variance Reduction Algorithms NIPS 2019
SGD Converges to Global Minimum in Deep Learning via Star-convex Path ICLR 2019
Gradient Information for Representation and Modeling NIPS 2019
Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels NIPS 2018
On Optimal Generalizability in Parametric Learning NIPS 2017