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ORCIDKiran Vodrahalli
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2020 – today
- 2025
[i10]Aishwarya Kamath, Johan Ferret, Shreya Pathak, Nino Vieillard, Ramona Merhej, Sarah Perrin, Tatiana Matejovicova, Alexandre Ramé, Morgane Rivière, Louis Rouillard, Thomas Mesnard, Geoffrey Cideron, Jean-Bastien Grill, Sabela Ramos, Edouard Yvinec, Michelle Casbon, Etienne Pot, Ivo Penchev, Gaël Liu, Francesco Visin, Kathleen Kenealy, Lucas Beyer, Xiaohai Zhai, Anton Tsitsulin, Róbert Busa-Fekete, Alex Feng, Noveen Sachdeva, Benjamin Coleman, Yi Gao, Basil Mustafa, Iain Barr, Emilio Parisotto, David Tian, Matan Eyal, Colin Cherry, Jan-Thorsten Peter, Danila Sinopalnikov, Surya Bhupatiraju, Rishabh Agarwal, Mehran Kazemi, Dan Malkin, Ravin Kumar, David Vilar, Idan Brusilovsky, Jiaming Luo, Andreas Steiner, Abe Friesen, Abhanshu Sharma, Abheesht Sharma, Adi Mayrav Gilady, Adrian Goedeckemeyer, Alaa Saade, Alexander Kolesnikov, Alexei Bendebury, Alvin Abdagic, Amit Vadi, András György, André Susano Pinto, Anil Das, Ankur Bapna, Antoine Miech, Antoine Yang, Antonia Paterson, Ashish Shenoy, Ayan Chakrabarti, Bilal Piot, Bo Wu, Bobak Shahriari, Bryce Petrini, Charlie Chen, Charline Le Lan, Christopher A. Choquette-Choo, CJ Carey, Cormac Brick, Daniel Deutsch, Danielle Eisenbud, Dee Cattle, Derek Cheng, Dimitris Paparas, Divyashree Shivakumar Sreepathihalli, Doug Reid, Dustin Tran, Dustin Zelle, Eric Noland, Erwin Huizenga, Eugene Kharitonov, Frederick Liu, Gagik Amirkhanyan, Glenn Cameron, Hadi Hashemi, Hanna Klimczak-Plucinska, Harman Singh, Harsh Mehta, Harshal Tushar Lehri, Hussein Hazimeh, Ian Ballantyne, Idan Szpektor, Ivan Nardini, Jean Pouget-Abadie, Jetha Chan, Joe Stanton, John Wieting, Jonathan Lai, Jordi Orbay, Joseph Fernandez, Josh Newlan, Ju-yeong Ji, Jyotinder Singh, Kat Black, Kathy Yu, Kevin Hui, Kiran Vodrahalli, Klaus Greff, Linhai Qiu, Marcella Valentine, Marina Coelho, Marvin Ritter, Matt Hoffman, Matthew Watson, Mayank Chaturvedi, Michael Moynihan, Min Ma, Nabila Babar, Natasha Noy, Nathan Byrd, Nick Roy, Nikola Momchev, Nilay Chauhan, Oskar Bunyan, Pankil Botarda, Paul Caron, Paul Kishan Rubenstein, Phil Culliton, Philipp Schmid, Pier Giuseppe Sessa, Pingmei Xu, Piotr Stanczyk, Pouya Tafti, Rakesh Shivanna, Renjie Wu, Renke Pan, Reza Rokni, Rob Willoughby, Rohith Vallu, Ryan Mullins, Sammy Jerome, Sara Smoot, Sertan Girgin, Shariq Iqbal, Shashir Reddy, Shruti Sheth, Siim Põder, Sijal Bhatnagar, Sindhu Raghuram Panyam, Sivan Eiger, Susan Zhang, Tianqi Liu, Trevor Yacovone, Tyler Liechty, Uday Kalra, Utku Evci, Vedant Misra, Vincent Roseberry, Vlad Feinberg, Vlad Kolesnikov, Woohyun Han, Woosuk Kwon, Xi Chen, Yinlam Chow, Yuvein Zhu, Zichuan Wei, Zoltan Egyed, Victor Cotruta, Minh Giang, Phoebe Kirk, Anand Rao, Jessica Lo, Erica Moreira, Luiz Gustavo Martins, Omar Sanseviero, Lucas Gonzalez, Zach Gleicher, Tris Warkentin, Vahab Mirrokni, Evan Senter, Eli Collins, Joelle K. Barral, Zoubin Ghahramani, Raia Hadsell, Yossi Matias, D. Sculley, Slav Petrov, Noah Fiedel, Noam Shazeer, Oriol Vinyals, Jeff Dean, Demis Hassabis, Koray Kavukcuoglu, Clément Farabet, Elena Buchatskaya, Jean-Baptiste Alayrac, Rohan Anil, Dmitry (Dima) Lepikhin, Sebastian Borgeaud, Olivier Bachem, Armand Joulin, Alek Andreev, Cassidy Hardin, Robert Dadashi, Léonard Hussenot:
Gemma 3 Technical Report. CoRR abs/2503.19786 (2025)- 2024
- [c10]Jon Schneider, Kiran Vodrahalli:
Online Learning with Bounded Recall. ICML 2024 - [i9]Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, Rohan Anil, Ethan Dyer, Siamak Shakeri, Roopali Vij, Harsh Mehta, Vinay V. Ramasesh, Quoc Le, Ed H. Chi, Yifeng Lu, Orhan Firat, Angeliki Lazaridou, Jean-Baptiste Lespiau, Nithya Attaluri, Kate Olszewska:
Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. CoRR abs/2409.12640 (2024) - 2023
- [c9]William Brown, Jon Schneider, Kiran Vodrahalli:
Is Learning in Games Good for the Learners? NeurIPS 2023 - [i8]William Brown, Jon Schneider, Kiran Vodrahalli:
Is Learning in Games Good for the Learners? CoRR abs/2305.19496 (2023) - 2022
- [b1]Kiran Vodrahalli:
Resource-Efficient Methods in Machine Learning. Columbia University, USA, 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
- [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) - [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 - [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
- [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 - [i4]Christos H. Papadimitriou, Kiran Vodrahalli, Mihalis Yannakakis:
The Platform Design Problem. CoRR abs/2009.06117 (2020)
2010 – 2019
- 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) - [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 - [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) - 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) - [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 - 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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