SI-DFA: Sub-expression integrated Deterministic Finite Automata for Deep Packet Inspection. - Ayesha Khalid; Rajat Sen; Anupam Chattopadhyay (HPSR, 2013)

Regret of Queueing Bandits. - Subhashini Krishnasamy; Rajat Sen; Ramesh Johari; Sanjay Shakkottai (NIPS, 2016)

Latent Contextual Bandits: A Non-Negative Matrix Factorization Approach. - Rajat Sen; Karthikeyan Shanmugam; Murat Kocaoglu; Alexandros G. Dimakis; Sanjay Shakkottai (CoRR, 2016)

Detecting Sponsored Recommendations. - Subhashini Krishnasamy; Rajat Sen; Sanjay Shakkottai; Sewoong Oh (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2016)

Contextual Bandits with Latent Confounders: An NMF Approach. - Rajat Sen; Karthikeyan Shanmugam; Murat Kocaoglu; Alexandros G. Dimakis; Sanjay Shakkottai (AISTATS, 2017)

Identifying Best Interventions through Online Importance Sampling. - Rajat Sen; Karthikeyan Shanmugam; Alexandros G. Dimakis; Sanjay Shakkottai (ICML, 2017)

Model-Powered Conditional Independence Test. - Rajat Sen; Ananda Theertha Suresh; Karthikeyan Shanmugam; Alexandros G. Dimakis; Sanjay Shakkottai (NIPS, 2017)

Causal Best Intervention Identification via Importance Sampling. - Rajat Sen; Karthikeyan Shanmugam; Alexandros G. Dimakis; Sanjay Shakkottai (CoRR, 2017)

Comprehensive design methodology for control and data planes in wavelength-routed optical networks. - Gitanjali Chandwani; Rajat Sen; Debasish Datta 001 (Photonic Netw. Commun., 2017)

Contextual Bandits with Stochastic Experts. - Rajat Sen; Karthikeyan Shanmugam; Sanjay Shakkottai (AISTATS, 2018)

Multi-Fidelity Black-Box Optimization with Hierarchical Partitions. - Rajat Sen; Kirthevasan Kandasamy; Sanjay Shakkottai (ICML, 2018)

Mimic and Classify : A meta-algorithm for Conditional Independence Testing. - Rajat Sen; Karthikeyan Shanmugam; Himanshu Asnani; Arman Rahimzamani; Sreeram Kannan (CoRR, 2018)

Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach. - Rajat Sen; Kirthevasan Kandasamy; Sanjay Shakkottai (CoRR, 2018)

Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach. - Rajat Sen; Kirthevasan Kandasamy; Sanjay Shakkottai (AISTATS, 2019)

Online Channel-state Clustering And Multiuser Capacity Learning For Wireless Scheduling. - Isfar Tariq; Rajat Sen; Gustavo de Veciana; Sanjay Shakkottai (INFOCOM, 2019)

Blocking Bandits. - Soumya Basu 001; Rajat Sen; Sujay Sanghavi; Sanjay Shakkottai (NeurIPS, 2019)

Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. - Rajat Sen; Hsiang-Fu Yu; Inderjit S. Dhillon (NeurIPS, 2019)

Importance Weighted Generative Networks. - Maurice Diesendruck; Ethan R. Elenberg; Rajat Sen; Guy W. Cole; Sanjay Shakkottai; Sinead A. Williamson (ECML/PKDD (2), 2019)

Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. - Matthew Faw; Rajat Sen; Karthikeyan Shanmugam; Constantine Caramanis; Sanjay Shakkottai (NeurIPS, 2020)

Top-k eXtreme Contextual Bandits with Arm Hierarchy. - Rajat Sen; Alexander Rakhlin; Lexing Ying; Rahul Kidambi; Dean P. Foster; Daniel N. Hill; Inderjit S. Dhillon (ICML, 2021)

Session-Aware Query Auto-completion using Extreme Multi-Label Ranking. - Nishant Yadav; Rajat Sen; Daniel N. Hill; Arya Mazumdar; Inderjit S. Dhillon (KDD, 2021)

Hierarchically Regularized Deep Forecasting. - Biswajit Paria; Rajat Sen; Amr Ahmed 001; Abhimanyu Das (CoRR, 2021)

Cluster-and-Conquer: A Framework For Time-Series Forecasting. - Reese Pathak; Rajat Sen; Nikhil Rao 001; N. Benjamin Erichson; Michael I. Jordan; Inderjit S. Dhillon (CoRR, 2021)

Learning Unknown Service Rates in Queues: A Multiarmed Bandit Approach. - Subhashini Krishnasamy; Rajat Sen; Ramesh Johari; Sanjay Shakkottai (Oper. Res., 2021)

Auto-Tuning for Cellular Scheduling Through Bandit-Learning and Low-Dimensional Clustering. - Isfar Tariq; Rajat Sen; Thomas David Novlan; Salam Akoum; Milap Majmundar; Gustavo de Veciana; Sanjay Shakkottai (IEEE/ACM Trans. Netw., 2021)

On the benefits of maximum likelihood estimation for Regression and Forecasting. - Pranjal Awasthi; Abhimanyu Das; Rajat Sen; Ananda Theertha Suresh (ICLR, 2022)

On Learning Mixture of Linear Regressions in the Non-Realizable Setting. - Soumyabrata Pal; Arya Mazumdar; Rajat Sen; Avishek Ghosh (ICML, 2022)

Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model. - Pranjal Awasthi; Abhimanyu Das; Weihao Kong; Rajat Sen (NeurIPS, 2022)

A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting. - Abhimanyu Das; Weihao Kong; Biswajit Paria; Rajat Sen (CoRR, 2022)

Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models. - Weihao Kong; Rajat Sen; Pranjal Awasthi; Abhimanyu Das (CoRR, 2022)

Efficient List-Decodable Regression using Batches. - Abhimanyu Das; Ayush Jain 001; Weihao Kong; Rajat Sen (ICML, 2023)

Blackbox optimization of unimodal functions. - Ashok Cutkosky; Abhimanyu Das; Weihao Kong; Chansoo Lee; Rajat Sen (UAI, 2023)

Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting. - Abhimanyu Das; Weihao Kong; Biswajit Paria; Rajat Sen (UAI, 2023)

Long-term Forecasting with TiDE: Time-series Dense Encoder. - Abhimanyu Das; Weihao Kong; Andrew Leach; Shaan Mathur; Rajat Sen; Rose Yu (Trans. Mach. Learn. Res., 2023)

Transformers can optimally learn regression mixture models. - Reese Pathak; Rajat Sen; Weihao Kong; Abhimanyu Das (ICLR, 2024)

A decoder-only foundation model for time-series forecasting. - Abhimanyu Das; Weihao Kong; Rajat Sen; Yichen Zhou (ICML, 2024)

A Combinatorial Approach to Robust PCA. - Weihao Kong; Mingda Qiao; Rajat Sen (ITCS, 2024)

Linear Regression using Heterogeneous Data Batches. - Ayush Jain 001; Rajat Sen; Weihao Kong; Abhimanyu Das; Alon Orlitsky (NeurIPS, 2024)

In-Context Fine-Tuning for Time-Series Foundation Models. - Abhimanyu Das; Matthew Faw; Rajat Sen; Yichen Zhou (CoRR, 2024)

Multi-Modal Forecaster: Jointly Predicting Time Series and Textual Data. - Kai Kim; Howard Tsai; Rajat Sen; Abhimanyu Das; Zihao Zhou; Abhishek Tanpure; Mathew Luo; Rose Yu (CoRR, 2024)

Bandits with Stochastic Experts: Constant Regret, Empirical Experts and Episodes. - Nihal Sharma; Rajat Sen; Soumya Basu 001; Karthikeyan Shanmugam; Sanjay Shakkottai (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2024)