← Authors

Rajat Sen

19 papers · 2016–2025 · 4 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (9) πŸ—ΊοΈ Taxonomy Completionist (27) 🐝 Cross-Pollinator (9) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ’Ž Century Club (19) πŸ—ƒοΈ Keyword Collector (82) πŸ”₯ Unstoppable (10)

Conferences

ICML (7) NIPS (7) AISTATS (3) ICLR (2)

Top co-authors

Sanjay Shakkottai (9) Abhimanyu Das (7) Weihao Kong (5) Karthikeyan Shanmugam (5) Yichen Zhou (2) Matthew Faw (2) Ananda Theertha Suresh (2) Ayush Jain (2) Kirthevasan Kandasamy (2) Pranjal Awasthi (2)

Research topics

Statistics (1)

Keywords

regret bound (6) online learning (3) contextual bandit (3) multi-armed bandit (3) stochastic optimization (2) black-box optimization (2) importance sampling (2) regret minimization (2) multi-fidelity optimization (2) linear regression (2) causal inference (2) hierarchical partitioning (2) expectation maximization (1) sample complexity (1) robust statistics (1) multi-label classification (1) parameter estimation (1) nearest neighbor (1) matrix factorization (1) adversarial robustness (1)

Papers

In-Context Fine-Tuning for Time-Series Foundation Models ICML 2025
Transformers can optimally learn regression mixture models ICLR 2024
Linear Regression using Heterogeneous Data Batches NIPS 2024
A decoder-only foundation model for time-series forecasting ICML 2024
Efficient List-Decodable Regression using Batches ICML 2023
On Learning Mixture of Linear Regressions in the Non-Realizable Setting ICML 2022
Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model NIPS 2022
On the benefits of maximum likelihood estimation for Regression and Forecasting ICLR 2022
Top-k eXtreme Contextual Bandits with Arm Hierarchy ICML 2021
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions NIPS 2020
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach AISTATS 2019
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting NIPS 2019
Blocking Bandits NIPS 2019
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions ICML 2018
Contextual Bandits with Stochastic Experts AISTATS 2018
Identifying Best Interventions through Online Importance Sampling ICML 2017
Contextual Bandits with Latent Confounders: An NMF Approach AISTATS 2017
Model-Powered Conditional Independence Test NIPS 2017
Regret of Queueing Bandits NIPS 2016