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Publication search results
found 150 matches
- 2024
- Pranjal Awasthi, Corinna Cortes, Mehryar Mohri
:
Best-effort adaptation. Ann. Math. Artif. Intell. 92(2): 393-438 (2024) - Pranjal Awasthi, Satyen Kale, Ankit Pensia:
Semi-supervised Group DRO: Combating Sparsity with Unlabeled Data. ALT 2024: 125-160 - Hanna Mazzawi, Pranjal Awasthi, Xavi Gonzalvo, Srikumar Ramalingam:
Simulated Overparameterization. CoRR abs/2402.05033 (2024) - Maximilian Böther, Abraham Sebastian, Pranjal Awasthi, Ana Klimovic, Srikumar Ramalingam:
On Distributed Larger-Than-Memory Subset Selection With Pairwise Submodular Functions. CoRR abs/2402.16442 (2024) - Naman Agarwal, Pranjal Awasthi, Satyen Kale, Eric Zhao:
Stacking as Accelerated Gradient Descent. CoRR abs/2403.04978 (2024) - Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun:
Position Coupling: Leveraging Task Structure for Improved Length Generalization of Transformers. CoRR abs/2405.20671 (2024) - 2023
- Pranjal Kumar
, Siddhartha Chauhan, Lalit Kumar Awasthi
:
Artificial Intelligence in Healthcare: Review, Ethics, Trust Challenges & Future Research Directions. Eng. Appl. Artif. Intell. 120: 105894 (2023) - Jordana J. George, Jie (Kevin) Yan, Dorothy E. Leidner, Pranjal Awasthi:
Does Engaging in Data Philanthropy Impact Business Value? Inf. Syst. Manag. 40(2): 112-126 (2023) - Sarabjeet Singh
, Neelam Surana
, Kailash Prasad
, Pranjali Jain
, Joycee Mekie
, Manu Awasthi
:
HyGain: High-performance, Energy-efficient Hybrid Gain Cell-based Cache Hierarchy. ACM Trans. Archit. Code Optim. 20(2): 24:1-24:20 (2023) - Pranjal Awasthi, Corinna Cortes, Christopher Mohri:
Theory and Algorithm for Batch Distribution Drift Problems. AISTATS 2023: 9826-9851 - Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong:
Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness. AISTATS 2023: 10077-10094 - Pranjal Awasthi, Nika Haghtalab, Eric Zhao:
Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes. COLT 2023: 5943-5949 - Pranjal Awasthi, Christopher Jung, Jamie Morgenstern:
Distributionally Robust Data Join. FORC 2023: 10:1-10:15 - Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan:
Agnostic Learning of General ReLU Activation Using Gradient Descent. ICLR 2023 - Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias:
Congested Bandits: Optimal Routing via Short-term Resets. CoRR abs/2301.09251 (2023) - Pranjal Awasthi, Corinna Cortes, Mehryar Mohri:
Best-Effort Adaptation. CoRR abs/2305.05816 (2023) - Pranjal Awasthi, Nika Haghtalab, Eric Zhao:
The Sample Complexity of Multi-Distribution Learning for VC Classes. CoRR abs/2307.12135 (2023) - Pranjal Awasthi, Anupam Gupta:
Improving Length-Generalization in Transformers via Task Hinting. CoRR abs/2310.00726 (2023) - Srikumar Ramalingam, Pranjal Awasthi, Sanjiv Kumar:
A Weighted K-Center Algorithm for Data Subset Selection. CoRR abs/2312.10602 (2023) - 2022
- Pranjal Kumar
, Siddhartha Chauhan, Lalit Kumar Awasthi
:
Human pose estimation using deep learning: review, methodologies, progress and future research directions. Int. J. Multim. Inf. Retr. 11(4): 489-521 (2022) - Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi:
Beyond GNNs: An Efficient Architecture for Graph Problems. AAAI 2022: 6019-6027 - Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan:
Understanding Simultaneous Train and Test Robustness. ALT 2022: 34-69 - Patrick O'Reilly, Pranjal Awasthi, Aravindan Vijayaraghavan, Bryan Pardo:
Effective and Inconspicuous Over-the-Air Adversarial Examples with Adaptive Filtering. ICASSP 2022: 6607-6611 - Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh:
On the benefits of maximum likelihood estimation for Regression and Forecasting. ICLR 2022 - Jacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Chris Russell, Jie Zhang:
Active Sampling for Min-Max Fairness. ICML 2022: 53-65 - Saba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian:
Individual Preference Stability for Clustering. ICML 2022: 197-246 - Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias:
Congested Bandits: Optimal Routing via Short-term Resets. ICML 2022: 1078-1100 - Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath:
Do More Negative Samples Necessarily Hurt In Contrastive Learning? ICML 2022: 1101-1116 - Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong:
H-Consistency Bounds for Surrogate Loss Minimizers. ICML 2022: 1117-1174 - Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi, Satyen Kale, Stefani Karp:
Agnostic Learnability of Halfspaces via Logistic Loss. ICML 2022: 10068-10103
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