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Abhishek Panigrahi
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2020 – today
- 2024
- [c10]Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia, Sanjeev Arora:
Trainable Transformer in Transformer. ICML 2024 - [i14]Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar:
Efficient Stagewise Pretraining via Progressive Subnetworks. CoRR abs/2402.05913 (2024) - [i13]Dan Friedman, Abhishek Panigrahi, Danqi Chen:
Representing Rule-based Chatbots with Transformers. CoRR abs/2407.10949 (2024) - [i12]Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel:
Progressive distillation induces an implicit curriculum. CoRR abs/2410.05464 (2024) - 2023
- [c9]Haoyu Zhao, Abhishek Panigrahi, Rong Ge, Sanjeev Arora:
Do Transformers Parse while Predicting the Masked Word? EMNLP 2023: 16513-16542 - [c8]Abhishek Panigrahi, Nikunj Saunshi, Haoyu Zhao, Sanjeev Arora:
Task-Specific Skill Localization in Fine-tuned Language Models. ICML 2023: 27011-27033 - [i11]Abhishek Panigrahi, Nikunj Saunshi, Haoyu Zhao, Sanjeev Arora:
Task-Specific Skill Localization in Fine-tuned Language Models. CoRR abs/2302.06600 (2023) - [i10]Haoyu Zhao, Abhishek Panigrahi, Rong Ge, Sanjeev Arora:
Do Transformers Parse while Predicting the Masked Word? CoRR abs/2303.08117 (2023) - [i9]Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia, Sanjeev Arora:
Trainable Transformer in Transformer. CoRR abs/2307.01189 (2023) - 2022
- [c7]Sanjeev Arora, Zhiyuan Li
, Abhishek Panigrahi:
Understanding Gradient Descent on the Edge of Stability in Deep Learning. ICML 2022: 948-1024 - [c6]Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi, Sanjeev Arora:
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms. NeurIPS 2022 - [i8]Sanjeev Arora, Zhiyuan Li, Abhishek Panigrahi:
Understanding Gradient Descent on Edge of Stability in Deep Learning. CoRR abs/2205.09745 (2022) - [i7]Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi, Sanjeev Arora:
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms. CoRR abs/2205.10287 (2022) - 2021
- [c5]Abhishek Panigrahi, Navin Goyal:
Learning and Generalization in RNNs. NeurIPS 2021: 21112-21124 - [i6]Abhishek Panigrahi, Navin Goyal:
Learning and Generalization in RNNs. CoRR abs/2106.00047 (2021) - 2020
- [c4]Abhishek Panigrahi, Abhishek Shetty, Navin Goyal:
Effect of Activation Functions on the Training of Overparametrized Neural Nets. ICLR 2020
2010 – 2019
- 2019
- [c3]Abhishek Panigrahi, Harsha Vardhan Simhadri, Chiranjib Bhattacharyya:
Word2Sense: Sparse Interpretable Word Embeddings. ACL (1) 2019: 5692-5705 - [c2]Suman Kalyan Maity, Abhishek Panigrahi, Sayan Ghosh, Arundhati Banerjee, Pawan Goyal, Animesh Mukherjee:
DeepTagRec: A Content-cum-User Based Tag Recommendation Framework for Stack Overflow. ECIR (2) 2019: 125-131 - [p1]Suman Kalyan Maity, Abhishek Panigrahi, Animesh Mukherjee:
Analyzing Social Book Reading Behavior on Goodreads and How It Predicts Amazon Best Sellers. Influence and Behavior Analysis in Social Networks and Social Media 2019: 211-235 - [i5]Suman Kalyan Maity, Abhishek Panigrahi, Sayan Ghosh, Arundhati Banerjee, Pawan Goyal, Animesh Mukherjee:
DeepTagRec: A Content-cum-User based Tag Recommendation Framework for Stack Overflow. CoRR abs/1903.03941 (2019) - [i4]Abhishek Panigrahi, Abhishek Shetty, Navin Goyal:
Effect of Activation Functions on the Training of Overparametrized Neural Nets. CoRR abs/1908.05660 (2019) - [i3]Abhishek Panigrahi, Raghav Somani
Non-Gaussianity of Stochastic Gradient Noise. CoRR abs/1910.09626 (2019) - 2018
- [i2]Suman Kalyan Maity, Abhishek Panigrahi, Animesh Mukherjee:
Analyzing Social Book Reading Behavior on Goodreads and how it predicts Amazon Best Sellers. CoRR abs/1809.07354 (2018) - [i1]Abhishek Panigrahi, Yueru Chen, C.-C. Jay Kuo:
Analysis on Gradient Propagation in Batch Normalized Residual Networks. CoRR abs/1812.00342 (2018) - 2017
- [c1]Suman Kalyan Maity, Abhishek Panigrahi, Animesh Mukherjee:
Book Reading Behavior on Goodreads Can Predict the Amazon Best Sellers. ASONAM 2017: 451-454
Coauthor Index
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