Abhimanyu Das

According to our database, Abhimanyu Das authored at least 49 papers between 2002 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Transformers can optimally learn regression mixture models.

Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das

CoRR, 2023

A decoder-only foundation model for time-series forecasting.

Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou

CoRR, 2023

Linear Regression using Heterogeneous Data Batches.

Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky

CoRR, 2023

Long-term Forecasting with TiDE: Time-series Dense Encoder.

Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu

CoRR, 2023

Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting.

Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Blackbox optimization of unimodal functions.

Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Efficient List-Decodable Regression using Batches.

Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen

Proceedings of the International Conference on Machine Learning, 2023

2022

Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models.

Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das

CoRR, 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 Generalized Linear Model.

Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the benefits of maximum likelihood estimation for Regression and Forecasting.

Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh

Proceedings of the Tenth International Conference on Learning Representations, 2022

Leveraging Initial Hints for Free in Stochastic Linear Bandits.

Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Qiuyi (Richard) Zhang

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Beyond GNNs: An Efficient Architecture for Graph Problems.

Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Hierarchically Regularized Deep Forecasting.

Biswajit Paria, Rajat Sen, Amr Ahmed, Abhimanyu Das

CoRR, 2021

A Convergence Analysis of Gradient Descent on Graph Neural Networks.

Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynamic Balancing for Model Selection in Bandits and RL.

Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit

Proceedings of the 38th International Conference on Machine Learning, 2021

Robust Pure Exploration in Linear Bandits with Limited Budget.

Ayya Alieva, Ashok Cutkosky, Abhimanyu Das

Proceedings of the 38th International Conference on Machine Learning, 2021

One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks.

Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Upper Confidence Bounds for Combining Stochastic Bandits.

Ashok Cutkosky, Abhimanyu Das, Manish Purohit

CoRR, 2020

Learning the gravitational force law and other analytic functions.

Atish Agarwala, Abhimanyu Das, Rina Panigrahy, Qiuyi Zhang

CoRR, 2020

On the Learnability of Random Deep Networks.

Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

2019

On the Learnability of Deep Random Networks.

Abhimanyu Das, Sreenivas Gollapudi, Ravi Kumar, Rina Panigrahy

CoRR, 2019

2018

Approximate Submodularity and its Applications: Subset Selection, Sparse Approximation and Dictionary Selection.

Abhimanyu Das, David Kempe

J. Mach. Learn. Res., 2018

Minimizing Latency in Online Ride and Delivery Services.

Abhimanyu Das, Sreenivas Gollapudi, Anthony Kim, Debmalya Panigrahi, Chaitanya Swamy

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

2016

STEPS: Predicting place attributes via spatio-temporal analysis.

Shuxin Nie, Abhimanyu Das, Evgeniy Gabrilovich, Wei-Lwun Lu, Boris Mazniker, Chris Schilling

CoRR, 2016

Information dissemination in heterogeneous-intent networks.

Abhimanyu Das, Sreenivas Gollapudi, Emre Kiciman, Onur Varol

Proceedings of the 8th ACM Conference on Web Science, 2016

2015

Approximate Modularity.

Flavio Chierichetti, Abhimanyu Das, Anirban Dasgupta, Ravi Kumar

Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

2014

Modeling opinion dynamics in social networks.

Abhimanyu Das, Sreenivas Gollapudi, Kamesh Munagala

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising.

Amr Ahmed, Abhimanyu Das, Alexander J. Smola

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Role of conformity in opinion dynamics in social networks.

Abhimanyu Das, Sreenivas Gollapudi, Arindam Khan, Renato Paes Leme

Proceedings of the second ACM conference on Online social networks, 2014

Ranking Twitter discussion groups.

James Cook, Abhimanyu Das, Krishnaram Kenthapadi, Nina Mishra

Proceedings of the second ACM conference on Online social networks, 2014

Discovering Topical Aspects in Microblogs.

Abhimanyu Das, Anitha Kannan

Proceedings of the COLING 2014, 2014

2013

Debiasing social wisdom.

Abhimanyu Das, Sreenivas Gollapudi, Rina Panigrahy, Mahyar Salek

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012

Selecting Diverse Features via Spectral Regularization.

Abhimanyu Das, Anirban Dasgupta, Ravi Kumar

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Factoring past exposure in display advertising targeting.

Neha Gupta, Abhimanyu Das, Sandeep Pandey, Vijay K. Narayanan

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Web-scale multi-task feature selection for behavioral targeting.

Amr Ahmed, Mohamed Aly, Abhimanyu Das, Alexander J. Smola, Tasos Anastasakos

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection.

Abhimanyu Das, David Kempe

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Estimating the Average of a Lipschitz-Continuous Function from One Sample.

Abhimanyu Das, David Kempe

Proceedings of the Algorithms, 2010

2008

Algorithms for subset selection in linear regression.

Abhimanyu Das, David Kempe

Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

Sensor Selection for Minimizing Worst-Case Prediction Error.

Abhimanyu Das, David Kempe

Proceedings of the 7th International Conference on Information Processing in Sensor Networks, 2008

2007

AMBROSia: An Autonomous Model-Based Reactive Observing System.

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

Proceedings of the Computational Science, 2007

2006

Adaptive Torque Control of Electro-rheological Fluid Brakes used in Active Knee Rehabilitation Devices.

Jason Nikitczuk, Abhimanyu Das, Harsh Vyas, Brian Weinberg, Constantinos Mavroidis

Proceedings of the 2006 IEEE International Conference on Robotics and Automation, 2006

A Generic Multi-scale Modeling Framework for Reactive Observing Systems: An Overview.

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

Proceedings of the Computational Science, 2006

2005

Data acquisition in multiple-sink sensor networks.

Abhimanyu Das, Debojyoti Dutta

ACM SIGMOBILE Mob. Comput. Commun. Rev., 2005

Low-state fairness: lower bounds and practical enforcement.

Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy, Ashish Goel, John S. Heidemann

Proceedings of the INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies, 2005

2004

On the Issues in Implementing the Peer Model in Integrated Optical Networks.

Vishal Sharma, Abhimanyu Das, Charles Chen

Photonic Netw. Commun., 2004

A low-state packet marking framework for approximate fair bandwidth allocation.

Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy

IEEE Commun. Lett., 2004

2003

Leveraging IP signaling and routing to manage UPSR-based transport networks.

Vishal Sharma, Abhimanyu Das, Charles Chen

Proceedings of IEEE International Conference on Communications, 2003

2002

Fair Stateless Aggregate Traffic Marking Using Active Queue Management Techniques.

Abhimanyu Das, Debojyoti Dutta, Ahmed Helmy

Proceedings of the Management of Multimedia on the Internet, 2002