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Kiran Vodrahalli
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Year
A Large Self-Annotated Corpus for Sarcasm
M Khodak, N Saunshi, K Vodrahalli
LREC 2018, 2017
1362017
Mapping between fMRI responses to movies and their natural language annotations
K Vodrahalli, PH Chen, Y Liang, C Baldassano, J Chen, E Yong, C Honey, ...
NeuroImage, 2017
58*2017
A compressed sensing view of unsupervised text embeddings, bag-of-n-grams, and LSTMs
S Arora, M Khodak, N Saunshi, K Vodrahalli
International Conference on Learning Representations (ICLR) 2018, 2018
432018
Learning to Plan with Logical Automata
B Araki, K Vodrahalli, T Leech, CI Vasile, M Donahue, D Rus
Robotics: Systems and Science (RSS) 2019, 2019
182019
Privacy accounting and quality control in the sage differentially private ML platform
M Lécuyer, R Spahn, K Vodrahalli, R Geambasu, D Hsu
Proceedings of the 27th ACM Symposium on Operating Systems Principles, 181-195, 2019
172019
The logical options framework
B Araki, X Li, K Vodrahalli, J DeCastro, M Fry, D Rus
International Conference on Machine Learning, 307-317, 2021
102021
Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior
B Araki, K Vodrahalli, T Leech, CI Vasile, M Donahue, D Rus
AAAI 2020, 2020
72020
Estimating Trending Topics on Twitter with Small Subsets of the Total Data
E Miller, K Vodrahalli, A Lee
Technical Report, 2015
52015
Attribute-efficient learning of monomials over highly-correlated variables
A Andoni, R Dudeja, D Hsu, K Vodrahalli
Algorithmic Learning Theory (ALT) 2019, 127-161, 2019
32019
Depth gradient based tracking
KN Vodrahalli
US Patent 9,367,731, 2016
32016
History-Restricted Online Learning
J Schneider, K Vodrahalli
arXiv preprint arXiv:2205.14519, 2022
2022
Nonlinear Initialization Methods for Low-Rank Neural Networks
K Vodrahalli, R Shivanna, M Sathiamoorthy, S Jain, E Chi
arXiv preprint arXiv:2202.00834, 2022
2022
Learning and planning with logical automata
B Araki, K Vodrahalli, T Leech, CI Vasile, M Donahue, D Rus
Autonomous Robots 45 (7), 1013-1028, 2021
2021
The Platform Design Problem
C Papadimitriou, K Vodrahalli, M Yannakakis
WINE 2021, 2021
2021
A Temporal Decay Model for Mapping between fMRI and Natural Language Annotations
K Vodrahalli, C Chen, V Mocz, C Baldassano, U Hasson, S Arora, ...
Computational and Cognitive Neuroscience (CCN 2017), 2018
2018
Temporally Dependent Mappings Between fMRI Responses and Natural Language Descriptions of Natural Stimuli
KN Vodrahalli
Princeton University, 2017
2017
A Semantic Shared Response Model
K Vodrahalli, PH Chen, J Chen, E Yong, C Honey, PJ Ramadge, ...
2016
Low-dimensional Representations of Semantic Context in Language and the Brain
K Vodrahalli
Princeton University, 2016
2016
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Articles 1–18