Arun Tejasvi Chaganty
Arun Tejasvi Chaganty
Google Inc.
Verified email at - Homepage
Cited by
Cited by
Spectral experts for estimating mixtures of linear regressions
AT Chaganty, P Liang
International Conference on Machine Learning, 1040-1048, 2013
Tensor factorization via matrix factorization
V Kuleshov, A Chaganty, P Liang
Artificial Intelligence and Statistics, 507-516, 2015
The price of debiasing automatic metrics in natural language evaluation
AT Chaganty, S Mussman, P Liang
arXiv preprint arXiv:1807.02202, 2018
Efficiently sampling probabilistic programs via program analysis
A Chaganty, A Nori, S Rajamani
Artificial Intelligence and Statistics, 153-160, 2013
Bootstrapped Self Training for Knowledge Base Population.
G Angeli, V Zhong, D Chen, AT Chaganty, J Bolton, MJJ Premkumar, ...
TAC, 2015
Estimating latent-variable graphical models using moments and likelihoods
AT Chaganty, P Liang
International Conference on Machine Learning, 1872-1880, 2014
On-the-job learning with bayesian decision theory
K Werling, A Chaganty, P Liang, C Manning
arXiv preprint arXiv:1506.03140, 2015
How much is 131 million dollars? putting numbers in perspective with compositional descriptions
AT Chaganty, P Liang
arXiv preprint arXiv:1609.00070, 2016
Stanford's 2013 KBP System.
G Angeli, AT Chaganty, AX Chang, K Reschke, J Tibshirani, J Wu, ...
TAC, 2013
Stanford at TAC KBP 2016: Sealing Pipeline Leaks and Understanding Chinese.
Y Zhang, AT Chaganty, A Paranjape, D Chen, J Bolton, P Qi, CD Manning
TAC, 2016
Combining relational learning with SMT solvers using CEGAR
A Chaganty, A Lal, AV Nori, SK Rajamani
International Conference on Computer Aided Verification, 447-462, 2013
TinkerBell: Cross-lingual Cold-Start Knowledge Base Construction.
M Al-Badrashiny, J Bolton, AT Chaganty, K Clark, C Harman, L Huang, ...
TAC, 2017
Importance sampling for unbiased on-demand evaluation of knowledge base population
A Chaganty, A Paranjape, P Liang, CD Manning
Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017
Textual analogy parsing: What's shared and what's compared among analogous facts
M Lamm, AT Chaganty, CD Manning, D Jurafsky, P Liang
arXiv preprint arXiv:1809.02700, 2018
Probabilistic model approximation for statistical relational learning
AT Chaganty, A Lal, AV Nori, S Rajamani
US Patent App. 13/308,571, 2013
Learning in a small world
AT Chaganty, P Gaur, B Ravindran
Proceedings of the 11th International Conference on Autonomous Agents and …, 2012
Simultaneous diagonalization: the asymmetric, low-rank, and noisy settings
V Kuleshov, AT Chaganty, P Liang
arXiv preprint arXiv:1501.06318, 2015
Quote attribution for literary text with neural networks
A Chaganty, G Muzny
Avaliable at http://cs224d. stanford. edu/reports/ChagantyArun. pdf, 2015
Mimic and Rephrase: Reflective listening in open-ended dialogue
J Dieter, T Wang, AT Chaganty, G Angeli, A Chang
Proceedings of the 23rd Conference on Computational Natural Language …, 2019
Estimating mixture models via mixtures of polynomials
S Wang, AT Chaganty, PS Liang
Advances in Neural Information Processing Systems 28, 487-495, 2015
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