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ORCIDChirag Pabbaraju
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2020 – today
- 2025
[c11]Moses Charikar, Spencer Compton, Chirag Pabbaraju:
Embedding Probability Distributions into Low Dimensional ℓ1: Tree Ising Models via Truncated Metrics. SODA 2025: 3210-3266- 2024
- [c10]Chirag Pabbaraju:
Multiclass Learnability Does Not Imply Sample Compression. ALT 2024: 930-944 - [i14]Moses Charikar, Chirag Pabbaraju, Kirankumar Shiragur:
Quantifying the Gain in Weak-to-Strong Generalization. CoRR abs/2405.15116 (2024) - [i13]Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju:
Credit Attribution and Stable Compression. CoRR abs/2406.15916 (2024) - [i12]Chirag Pabbaraju, Sahasrajit Sarmasarkar:
A Characterization of List Regression. CoRR abs/2409.19218 (2024) - [i11]Moses Charikar, Chirag Pabbaraju:
Exploring Facets of Language Generation in the Limit. CoRR abs/2411.15364 (2024) - 2023
- [c9]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Pitfalls of Gaussians as a noise distribution in NCE. ICLR 2023 - [c8]Guy Blanc, Jane Lange, Chirag Pabbaraju, Colin Sullivan, Li-Yang Tan, Mo Tiwari:
Harnessing the power of choices in decision tree learning. NeurIPS 2023 - [c7]Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski:
Provable benefits of score matching. NeurIPS 2023 - [c6]Moses Charikar
, Chirag Pabbaraju:
A Characterization of List Learnability. STOC 2023: 1713-1726 - [i10]Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski:
Provable benefits of score matching. CoRR abs/2306.01993 (2023) - [i9]Chirag Pabbaraju:
Multiclass Learnability Does Not Imply Sample Compression. CoRR abs/2308.06424 (2023) - [i8]Guy Blanc, Jane Lange, Chirag Pabbaraju, Colin Sullivan, Li-Yang Tan, Mo Tiwari:
Harnessing the Power of Choices in Decision Tree Learning. CoRR abs/2310.01551 (2023) - [i7]Shivam Garg, Chirag Pabbaraju, Kirankumar Shiragur, Gregory Valiant:
Testing with Non-identically Distributed Samples. CoRR abs/2311.11194 (2023) - [i6]Moses Charikar, Spencer Compton, Chirag Pabbaraju:
Average-Case Dimensionality Reduction in 𝓁1: Tree Ising Models. CoRR abs/2312.02435 (2023) - 2022
- [i5]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Pitfalls of Gaussians as a noise distribution in NCE. CoRR abs/2210.00189 (2022) - [i4]Moses Charikar, Chirag Pabbaraju:
A Characterization of List Learnability. CoRR abs/2211.04956 (2022) - 2021
- [c5]Chirag Pabbaraju, Ezra Winston, J. Zico Kolter:
Estimating Lipschitz constants of monotone deep equilibrium models. ICLR 2021 - [c4]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Universal Approximation Using Well-Conditioned Normalizing Flows. NeurIPS 2021: 12700-12711 - [i3]Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski:
Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flows. CoRR abs/2107.02951 (2021) - 2020
- [c3]Chirag Pabbaraju, Po-Wei Wang, J. Zico Kolter:
Efficient semidefinite-programming-based inference for binary and multi-class MRFs. NeurIPS 2020 - [i2]Chirag Pabbaraju, Po-Wei Wang, J. Zico Kolter:
Efficient semidefinite-programming-based inference for binary and multi-class MRFs. CoRR abs/2012.02661 (2020)
2010 – 2019
- 2019
- [c2]Shishir G. Patil, Don Kurian Dennis, Chirag Pabbaraju, Nadeem Shaheer, Harsha Vardhan Simhadri, Vivek Seshadri, Manik Varma, Prateek Jain:
GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users. UIST 2019: 403-415 - [i1]Chirag Pabbaraju, Prateek Jain:
Learning Functions over Sets via Permutation Adversarial Networks. CoRR abs/1907.05638 (2019) - 2018
- [c1]Don Kurian Dennis, Chirag Pabbaraju, Harsha Vardhan Simhadri, Prateek Jain:
Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices. NeurIPS 2018: 10976-10987
Coauthor Index
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