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Kiran Vodrahalli
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Books and Theses
- 2022
- [b1]Kiran Vodrahalli:
Resource-Efficient Methods in Machine Learning. Columbia University, USA, 2022
Journal Articles
- 2021
- [j3]Brandon Araki
, Kiran Vodrahalli, Thomas Leech, Cristian-Ioan Vasile
, Mark Donahue, Daniela Rus:
Learning and planning with logical automata. Auton. Robots 45(7): 1013-1028 (2021) - 2019
- [j2]Mathias Lécuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu:
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform. ACM SIGOPS Oper. Syst. Rev. 53(1): 75-84 (2019) - 2018
- [j1]Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang, Christopher Baldassano
, Janice Chen, Esther Yong, Christopher J. Honey
, Uri Hasson
, Peter J. Ramadge, Kenneth A. Norman, Sanjeev Arora:
Mapping between fMRI responses to movies and their natural language annotations. NeuroImage 180(Part): 223-231 (2018)
Conference and Workshop Papers
- 2023
- [c9]William Brown, Jon Schneider, Kiran Vodrahalli:
Is Learning in Games Good for the Learners? NeurIPS 2023 - 2021
- [c8]Brandon Araki, Xiao Li, Kiran Vodrahalli, Jonathan A. DeCastro, Micah J. Fry, Daniela Rus:
The Logical Options Framework. ICML 2021: 307-317 - [c7]Christos Harilaos Papadimitriou, Kiran Vodrahalli, Mihalis Yannakakis:
The Platform Design Problem. WINE 2021: 317-333 - 2020
- [c6]Brandon Araki, Kiran Vodrahalli, Thomas Leech, Cristian Ioan Vasile, Mark Donahue, Daniela Rus:
Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior. AAAI 2020: 10026-10034 - 2019
- [c5]Alexandr Andoni, Rishabh Dudeja, Daniel Hsu, Kiran Vodrahalli:
Attribute-efficient learning of monomials over highly-correlated variables. ALT 2019: 127-161 - [c4]Brandon Araki, Kiran Vodrahalli, Thomas Leech, Cristian Ioan Vasile
, Mark Donahue, Daniela Rus:
Learning to Plan with Logical Automata. Robotics: Science and Systems 2019 - [c3]Mathias Lécuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu:
Privacy accounting and quality control in the sage differentially private ML platform. SOSP 2019: 181-195 - 2018
- [c2]Sanjeev Arora, Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli:
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs. ICLR (Poster) 2018 - [c1]Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli:
A Large Self-Annotated Corpus for Sarcasm. LREC 2018
Informal and Other Publications
- 2023
- [i8]William Brown, Jon Schneider, Kiran Vodrahalli:
Is Learning in Games Good for the Learners? CoRR abs/2305.19496 (2023) - 2022
- [i7]Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, Ed H. Chi:
Algorithms for Efficiently Learning Low-Rank Neural Networks. CoRR abs/2202.00834 (2022) - [i6]Jon Schneider, Kiran Vodrahalli:
History-Restricted Online Learning. CoRR abs/2205.14519 (2022) - 2021
- [i5]Brandon Araki, Xiao Li, Kiran Vodrahalli, Jonathan A. DeCastro, Micah J. Fry, Daniela Rus:
The Logical Options Framework. CoRR abs/2102.12571 (2021) - 2020
- [i4]Christos H. Papadimitriou, Kiran Vodrahalli, Mihalis Yannakakis:
The Platform Design Problem. CoRR abs/2009.06117 (2020) - 2019
- [i3]Mathias Lécuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu:
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform. CoRR abs/1909.01502 (2019) - 2017
- [i2]Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli:
A Large Self-Annotated Corpus for Sarcasm. CoRR abs/1704.05579 (2017) - 2016
- [i1]Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang, Janice Chen, Esther Yong, Christopher J. Honey, Peter J. Ramadge, Kenneth A. Norman, Sanjeev Arora:
Mapping Between Natural Movie fMRI Responses and Word-Sequence Representations. CoRR abs/1610.03914 (2016)
Coauthor Index
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