Abhimanyu Das - RankMe

65 papers A* 21A 5B 2Misc 3Journal 26Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	In-Context Fine-Tuning for Time-Series Foundation Models. ICML Matthew Faw, Rajat Sen, Yichen Zhou, Abhimanyu Das
2024	A*	`conf`	A decoder-only foundation model for time-series forecasting. ICML Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou
2024	J	`jnl`	In-Context Fine-Tuning for Time-Series Foundation Models. CoRR Abhimanyu Das, Matthew Faw, Rajat Sen, Yichen Zhou
2024	A*	`conf`	Linear Regression using Heterogeneous Data Batches. NeurIPS Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky
2024	J	`jnl`	Multi-Modal Forecaster: Jointly Predicting Time Series and Textual Data. CoRR Kai Kim, Howard Tsai, Rajat Sen, Abhimanyu Das, Zihao Zhou, Abhishek Tanpure, Mathew Luo, Rose Yu
2024	A*	`conf`	Transformers can optimally learn regression mixture models. ICLR Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das
2023	J	`jnl`	A decoder-only foundation model for time-series forecasting. CoRR Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou
2023	A	`conf`	Blackbox optimization of unimodal functions. UAI Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen
2023	A	`conf`	Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting. UAI Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
2023	A*	`conf`	Efficient List-Decodable Regression using Batches. ICML Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen
2023	J	`jnl`	Linear Regression using Heterogeneous Data Batches. CoRR Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky
2023	J	`jnl`	Long-term Forecasting with TiDE: Time-series Dense Encoder. CoRR Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu
2023	J	`jnl`	Long-term Forecasting with TiDE: Time-series Dense Encoder. Trans. Mach. Learn. Res. Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu
2023	J	`jnl`	Transformers can optimally learn regression mixture models. CoRR Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das
2022	J	`jnl`	A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting. CoRR Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
2022	A*	`conf`	Beyond GNNs: An Efficient Architecture for Graph Problems. AAAI Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi
2022	J	`jnl`	Efficient List-Decodable Regression using Batches. CoRR Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen
2022	B	`conf`	Leveraging Initial Hints for Free in Stochastic Linear Bandits. ALT Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Qiuyi (Richard) Zhang
2022	J	`jnl`	Leveraging Initial Hints for Free in Stochastic Linear Bandits. CoRR Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Qiuyi (Richard) Zhang
2022	A*	`conf`	On the benefits of maximum likelihood estimation for Regression and Forecasting. ICLR Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh
2022	A*	`conf`	Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model. NeurIPS Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen
2022	J	`jnl`	Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models. CoRR Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das
2021	A*	`conf`	A Convergence Analysis of Gradient Descent on Graph Neural Networks. NeurIPS Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi
2021	A*	`conf`	Dynamic Balancing for Model Selection in Bandits and RL. ICML Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit
2021	J	`jnl`	Hierarchically Regularized Deep Forecasting. CoRR Biswajit Paria, Rajat Sen, Amr Ahmed, Abhimanyu Das
2021	J	`jnl`	On the benefits of maximum likelihood estimation for Regression and Forecasting. CoRR Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh
2021	A*	`conf`	One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks. ICLR Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
2021	J	`jnl`	One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks. CoRR Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
2021	A*	`conf`	Robust Pure Exploration in Linear Bandits with Limited Budget. ICML Ayya Alieva, Ashok Cutkosky, Abhimanyu Das
2020	J	`jnl`	Learning the gravitational force law and other analytic functions. CoRR Atish Agarwala, Abhimanyu Das, Rina Panigrahy, Qiuyi Zhang
2020	A*	`conf`	On the Learnability of Random Deep Networks. SODA Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy
2020	J	`jnl`	Upper Confidence Bounds for Combining Stochastic Bandits. CoRR Ashok Cutkosky, Abhimanyu Das, Manish Purohit
2019	J	`jnl`	On the Learnability of Deep Random Networks. CoRR Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy
2018	J	`jnl`	Approximate Submodularity and its Applications: Subset Selection, Sparse Approximation and Dictionary Selection. J. Mach. Learn. Res. Abhimanyu Das, David Kempe
2018	A*	`conf`	Minimizing Latency in Online Ride and Delivery Services. WWW Abhimanyu Das, Sreenivas Gollapudi, Anthony Kim, Debmalya Panigrahi, Chaitanya Swamy
2018	J	`jnl`	Minimizing Latency in Online Ride and Delivery Services. CoRR Abhimanyu Das, Sreenivas Gollapudi, Anthony Kim, Debmalya Panigrahi, Chaitanya Swamy
2016	—	`conf`	Information dissemination in heterogeneous-intent networks. WebSci Abhimanyu Das, Sreenivas Gollapudi, Emre Kiciman, Onur Varol
2016	J	`jnl`	STEPS: Predicting place attributes via spatio-temporal analysis. CoRR Shuxin Nie, Abhimanyu Das, Evgeniy Gabrilovich, Wei-Lwun Lu, Boris Mazniker, Chris Schilling
2015	A*	`conf`	Approximate Modularity. FOCS Flavio Chierichetti, Abhimanyu Das, Anirban Dasgupta, Ravi Kumar
2014	B	`conf`	Discovering Topical Aspects in Microblogs. COLING Abhimanyu Das, Anitha Kannan
2014	A	`conf`	Modeling opinion dynamics in social networks. WSDM Abhimanyu Das, Sreenivas Gollapudi, Kamesh Munagala
2014	—	`conf`	Ranking Twitter discussion groups. COSN James Cook, Abhimanyu Das, Krishnaram Kenthapadi, Nina Mishra
2014	—	`conf`	Role of conformity in opinion dynamics in social networks. COSN Abhimanyu Das, Sreenivas Gollapudi, Arindam Khan, Renato Paes Leme
2014	A	`conf`	Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising. WSDM Amr Ahmed, Abhimanyu Das, Alexander J. Smola
2013	A*	`conf`	Debiasing social wisdom. KDD Abhimanyu Das, Sreenivas Gollapudi, Rina Panigrahy, Mahyar Salek
2012	A*	`conf`	Factoring past exposure in display advertising targeting. KDD Neha Gupta, Abhimanyu Das, Sandeep Pandey, Vijay K. Narayanan
2012	—	`conf`	Selecting Diverse Features via Spectral Regularization. NIPS Abhimanyu Das, Anirban Dasgupta, Ravi Kumar
2012	A	`conf`	Web-scale multi-task feature selection for behavioral targeting. CIKM Amr Ahmed, Mohamed Aly, Abhimanyu Das, Alexander J. Smola, Tasos Anastasakos
2011	J	`jnl`	Estimating the Average of a Lipschitz-Continuous Function from One Sample CoRR Abhimanyu Das, David Kempe
2011	J	`jnl`	Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection CoRR Abhimanyu Das, David Kempe
2011	A*	`conf`	Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection. ICML Abhimanyu Das, David Kempe
2010	—	`conf`	Estimating the Average of a Lipschitz-Continuous Function from One Sample. ESA (1) Abhimanyu Das, David Kempe
2008	A*	`conf`	Algorithms for subset selection in linear regression. STOC Abhimanyu Das, David Kempe
2008	—	`conf`	Sensor Selection for Minimizing Worst-Case Prediction Error. IPSN Abhimanyu Das, David Kempe
2007	Misc	`conf`	AMBROSia: An Autonomous Model-Based Reactive Observing System. International Conference on Computational Science (1) David A. Caron, Abhimanyu Das, Amit Dhariwal, Leana Golubchik, Ramesh Govindan, David Kempe, Carl Oberg, Abhishek B. Sharma, Beth Stauffer, Gaurav S. Sukhatme, Bin Zhang
2006	Misc	`conf`	A Generic Multi-scale Modeling Framework for Reactive Observing Systems: An Overview. International Conference on Computational Science (3) Leana Golubchik, David A. Caron, Abhimanyu Das, Amit Dhariwal, Ramesh Govindan, David Kempe, Carl Oberg, Abhishek B. Sharma, Beth Stauffer, Gaurav S. Sukhatme, Bin Zhang
2006	A*	`conf`	Adaptive Torque Control of Electro-rheological Fluid Brakes used in Active Knee Rehabilitation Devices. ICRA Jason Nikitczuk, Abhimanyu Das, Harsh Vyas, Brian Weinberg, Constantinos Mavroidis
2005	J	`jnl`	Data acquisition in multiple-sink sensor networks. ACM SIGMOBILE Mob. Comput. Commun. Rev. Abhimanyu Das, Debojyoti Dutta
2005	A*	`conf`	Low-state fairness: lower bounds and practical enforcement. INFOCOM Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy, Ashish Goel, John S. Heidemann
2004	J	`jnl`	A low-state packet marking framework for approximate fair bandwidth allocation. IEEE Commun. Lett. Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy
2004	Misc	`conf`	Data acquisition in multiple-sink sensor networks. SenSys Abhimanyu Das, Debojyoti Dutta
2004	J	`jnl`	On the Issues in Implementing the Peer Model in Integrated Optical Networks. Photonic Netw. Commun. Vishal Sharma, Abhimanyu Das, Charles Chen
2003	—	`conf`	Leveraging IP signaling and routing to manage UPSR-based transport networks. ICC Vishal Sharma, Abhimanyu Das, Charles Chen
2002	—	`conf`	Fair Stateless Aggregate Traffic Marking Using Active Queue Management Techniques. MMNS Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy
2002	J	`jnl`	Fair Stateless Aggregate Traffic Marking using Active Queue Management Techniques CoRR Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy