Chirag Pabbaraju
Chirag Pabbaraju
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Multiple instance learning for efficient sequential data classification on resource-constrained devices
D Dennis, C Pabbaraju, HV Simhadri, P Jain
Advances in Neural Information Processing Systems 31, 2018
Gesturepod: Enabling on-device gesture-based interaction for white cane users
SG Patil, DK Dennis, C Pabbaraju, N Shaheer, HV Simhadri, V Seshadri, ...
Proceedings of the 32nd Annual ACM Symposium on User Interface Software and …, 2019
Estimating Lipschitz constants of monotone deep equilibrium models
C Pabbaraju, E Winston, JZ Kolter
International Conference on Learning Representations, 2020
Universal approximation for log-concave distributions using well-conditioned normalizing flows
H Lee, C Pabbaraju, A Sevekari, A Risteski
arXiv preprint arXiv:2107.02951, 2021
Learning functions over sets via permutation adversarial networks
C Pabbaraju, P Jain
arXiv preprint arXiv:1907.05638, 2019
A characterization of list learnability
M Charikar, C Pabbaraju
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 1713-1726, 2023
Pitfalls of Gaussians as a noise distribution in NCE
H Lee, C Pabbaraju, A Sevekari, A Risteski
arXiv preprint arXiv:2210.00189, 2022
Efficient semidefinite-programming-based inference for binary and multi-class MRFs
C Pabbaraju, PW Wang, JZ Kolter
Advances in Neural Information Processing Systems 33, 4259-4270, 2020
Testing with Non-identically Distributed Samples
S Garg, C Pabbaraju, K Shiragur, G Valiant
arXiv preprint arXiv:2311.11194, 2023
Harnessing the Power of Choices in Decision Tree Learning
G Blanc, J Lange, C Pabbaraju, C Sullivan, LY Tan, M Tiwari
arXiv preprint arXiv:2310.01551, 2023
Multiclass Learnability Does Not Imply Sample Compression
C Pabbaraju
arXiv preprint arXiv:2308.06424, 2023
Provable benefits of score matching
C Pabbaraju, D Rohatgi, A Sevekari, H Lee, A Moitra, A Risteski
arXiv preprint arXiv:2306.01993, 2023
Image segmention via efficient semidefinate-programming based inference for binary and multi-class Markov Random Fields
DT Willmott, C Pabbaraju, PW Wang, J Kolter
US Patent 11,587,237, 2023
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