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ORCIDRajat Sen
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2020 – today
- 2024
[j6]Nihal Sharma
, Rajat Sen, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai:
Bandits with Stochastic Experts: Constant Regret, Empirical Experts and Episodes. ACM Trans. Model. Perform. Evaluation Comput. Syst. 9(3): 12:1-12:33 (2024)- [c26]Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das:
Transformers can optimally learn regression mixture models. ICLR 2024 - [c25]Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou:
A decoder-only foundation model for time-series forecasting. ICML 2024 - [c24]Weihao Kong, Mingda Qiao, Rajat Sen:
A Combinatorial Approach to Robust PCA. ITCS 2024: 70:1-70:22 - [c23]Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky:
Linear Regression using Heterogeneous Data Batches. NeurIPS 2024 - [i28]Abhimanyu Das, Matthew Faw, Rajat Sen, Yichen Zhou:
In-Context Fine-Tuning for Time-Series Foundation Models. CoRR abs/2410.24087 (2024) - [i27]Kai Kim, Howard Tsai, Rajat Sen, Abhimanyu Das, Zihao Zhou, Abhishek Tanpure, Mathew Luo, Rose Yu:
Multi-Modal Forecaster: Jointly Predicting Time Series and Textual Data. CoRR abs/2411.06735 (2024) - 2023
- [j5]Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu:
Long-term Forecasting with TiDE: Time-series Dense Encoder. Trans. Mach. Learn. Res. 2023 (2023) - [c22]Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen:
Efficient List-Decodable Regression using Batches. ICML 2023: 7025-7065 - [c21]Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen:
Blackbox optimization of unimodal functions. UAI 2023: 476-484 - [c20]Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen:
Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting. UAI 2023: 518-528 - [i26]Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu:
Long-term Forecasting with TiDE: Time-series Dense Encoder. CoRR abs/2304.08424 (2023) - [i25]Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky:
Linear Regression using Heterogeneous Data Batches. CoRR abs/2309.01973 (2023) - [i24]Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou:
A decoder-only foundation model for time-series forecasting. CoRR abs/2310.10688 (2023) - [i23]Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das:
Transformers can optimally learn regression mixture models. CoRR abs/2311.08362 (2023) - [i22]Weihao Kong, Mingda Qiao, Rajat Sen:
A Combinatorial Approach to Robust PCA. CoRR abs/2311.16416 (2023) - 2022
- [c19]Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh:
On the benefits of maximum likelihood estimation for Regression and Forecasting. ICLR 2022 - [c18]Soumyabrata Pal, Arya Mazumdar, Rajat Sen, Avishek Ghosh:
On Learning Mixture of Linear Regressions in the Non-Realizable Setting. ICML 2022: 17202-17220 - [c17]Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen:
Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model. NeurIPS 2022 - [i21]Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen:
A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting. CoRR abs/2204.10414 (2022) - [i20]Avishek Ghosh, Arya Mazumdar, Soumyabrata Pal, Rajat Sen:
On Learning Mixture of Linear Regressions in the Non-Realizable Setting. CoRR abs/2205.13166 (2022) - [i19]Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das:
Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models. CoRR abs/2206.04777 (2022) - [i18]Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen:
Efficient List-Decodable Regression using Batches. CoRR abs/2211.12743 (2022) - 2021
- [j4]Subhashini Krishnasamy, Rajat Sen, Ramesh Johari, Sanjay Shakkottai:
Learning Unknown Service Rates in Queues: A Multiarmed Bandit Approach. Oper. Res. 69(1): 315-330 (2021) - [j3]Isfar Tariq, Rajat Sen, Thomas David Novlan, Salam Akoum, Milap Majmundar, Gustavo de Veciana, Sanjay Shakkottai:
Auto-Tuning for Cellular Scheduling Through Bandit-Learning and Low-Dimensional Clustering. IEEE/ACM Trans. Netw. 29(5): 1933-1947 (2021) - [c16]Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon:
Top-k eXtreme Contextual Bandits with Arm Hierarchy. ICML 2021: 9422-9433 - [c15]Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon:
Session-Aware Query Auto-completion using Extreme Multi-Label Ranking. KDD 2021: 3835-3844 - [i17]Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon:
Top-k eXtreme Contextual Bandits with Arm Hierarchy. CoRR abs/2102.07800 (2021) - [i16]Biswajit Paria, Rajat Sen, Amr Ahmed, Abhimanyu Das:
Hierarchically Regularized Deep Forecasting. CoRR abs/2106.07630 (2021) - [i15]Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh:
On the benefits of maximum likelihood estimation for Regression and Forecasting. CoRR abs/2106.10370 (2021) - [i14]Reese Pathak, Rajat Sen, Nikhil Rao, N. Benjamin Erichson, Michael I. Jordan, Inderjit S. Dhillon:
Cluster-and-Conquer: A Framework For Time-Series Forecasting. CoRR abs/2110.14011 (2021) - 2020
- [c14]Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai:
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. NeurIPS 2020 - [i13]Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon:
Session-Aware Query Auto-completion using Extreme Multi-label Ranking. CoRR abs/2012.07654 (2020)
2010 – 2019
- 2019
- [c13]Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai:
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach. AISTATS 2019: 2096-2105 - [c12]Isfar Tariq, Rajat Sen, Gustavo de Veciana, Sanjay Shakkottai:
Online Channel-state Clustering And Multiuser Capacity Learning For Wireless Scheduling. INFOCOM 2019: 136-144 - [c11]Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai:
Blocking Bandits. NeurIPS 2019: 4785-4794 - [c10]Rajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon:
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. NeurIPS 2019: 4838-4847 - [c9]Maurice Diesendruck, Ethan R. Elenberg, Rajat Sen, Guy W. Cole, Sanjay Shakkottai, Sinead A. Williamson:
Importance Weighted Generative Networks. ECML/PKDD (2) 2019: 249-265 - [i12]Rajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon:
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. CoRR abs/1905.03806 (2019) - [i11]Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai:
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. CoRR abs/1907.10154 (2019) - [i10]Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai:
Blocking Bandits. CoRR abs/1907.11975 (2019) - 2018
- [c8]Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai:
Contextual Bandits with Stochastic Experts. AISTATS 2018: 852-861 - [c7]Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai:
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions. ICML 2018: 4545-4554 - [i9]Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai:
Contextual Bandits with Stochastic Experts. CoRR abs/1802.08737 (2018) - [i8]Maurice Diesendruck, Ethan R. Elenberg, Rajat Sen, Guy W. Cole, Sanjay Shakkottai, Sinead A. Williamson:
Importance weighted generative networks. CoRR abs/1806.02512 (2018) - [i7]Rajat Sen, Karthikeyan Shanmugam, Himanshu Asnani, Arman Rahimzamani, Sreeram Kannan:
Mimic and Classify : A meta-algorithm for Conditional Independence Testing. CoRR abs/1806.09708 (2018) - [i6]Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai:
Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach. CoRR abs/1810.10482 (2018) - 2017
- [j2]Gitanjali Chandwani, Rajat Sen, Debasish Datta:
Comprehensive design methodology for control and data planes in wavelength-routed optical networks. Photonic Netw. Commun. 33(3): 243-257 (2017) - [c6]Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai:
Contextual Bandits with Latent Confounders: An NMF Approach. AISTATS 2017: 518-527 - [c5]Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Identifying Best Interventions through Online Importance Sampling. ICML 2017: 3057-3066 - [c4]Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Model-Powered Conditional Independence Test. NIPS 2017: 2951-2961 - [i5]Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Causal Best Intervention Identification via Importance Sampling. CoRR abs/1701.02789 (2017) - [i4]Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Model-Powered Conditional Independence Test. CoRR abs/1709.06138 (2017) - 2016
- [j1]Subhashini Krishnasamy, Rajat Sen, Sanjay Shakkottai, Sewoong Oh:
Detecting Sponsored Recommendations. ACM Trans. Model. Perform. Evaluation Comput. Syst. 2(1): 6:1-6:29 (2016) - [c3]Subhashini Krishnasamy, Rajat Sen, Ramesh Johari, Sanjay Shakkottai:
Regret of Queueing Bandits. NIPS 2016: 1669-1677 - [i3]Subhashini Krishnasamy, Rajat Sen, Ramesh Johari, Sanjay Shakkottai:
Regret of Queueing Bandits. CoRR abs/1604.06377 (2016) - [i2]Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai:
Latent Contextual Bandits: A Non-Negative Matrix Factorization Approach. CoRR abs/1606.00119 (2016) - 2015
- [c2]Subhashini Krishnasamy, Rajat Sen, Sewoong Oh, Sanjay Shakkottai:
Detecting Sponsored Recommendations. SIGMETRICS 2015: 445-446 - [i1]Subhashini Krishnasamy, Rajat Sen, Sewoong Oh, Sanjay Shakkottai:
Detecting Sponsored Recommendations. CoRR abs/1504.03713 (2015) - 2013
- [c1]Ayesha Khalid, Rajat Sen, Anupam Chattopadhyay:
SI-DFA: Sub-expression integrated Deterministic Finite Automata for Deep Packet Inspection. HPSR 2013: 164-170
Coauthor Index
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