Seuraa
Andrej Risteski
Andrej Risteski
Carnegie Mellon University
Vahvistettu sähköpostiosoite verkkotunnuksessa andrew.cmu.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
A latent variable model approach to PMI-based word embeddings
S Arora, Y Li, Y Liang, T Ma, A Risteski
Transactions of the Association for Computational Linguistics 4, 385-399, 2016
594*2016
Linear algebraic structure of word senses, with applications to polysemy
S Arora, Y Li, Y Liang, T Ma, A Risteski
Transactions of the Association of Computational Linguistics 6, 483-495, 2018
2232018
The Risks of Invariant Risk Minimization
E Rosenfeld, P Ravikumar, A Risteski
International Conference on Learning Representations (ICLR), 2020, 2020
2042020
Do GANs learn the distribution? some theory and empirics
S Arora, A Risteski, Y Zhang
International Conference on Learning Representations (ICLR), 2019, 2018
174*2018
On the ability of neural nets to express distributions
H Lee, R Ge, T Ma, A Risteski, S Arora
Conference on Learning Theory, 1271-1296, 2017
822017
Approximability of Discriminators Implies Diversity in GANs
Y Bai, T Ma, A Risteski
International Conference on Learning Representations (ICLR), 2020, 2018
722018
Automated WordNet Construction Using Word Embeddings
M Khodak, A Risteski, C Fellbaum, S Arora
Proceedings of the 1st Workshop on Sense, Concept and Entity Representations …, 2017
47*2017
Beyond log-concavity: Provable guarantees for sampling multi-modal distributions using simulated tempering langevin monte carlo
H Lee, A Risteski, R Ge
Advances in neural information processing systems 31, 7847-7856, 2018
42*2018
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization
E Rosenfeld, P Ravikumar, A Risteski
arXiv preprint arXiv:2202.06856, 2022
402022
Provable learning of noisy-or networks
S Arora, R Ge, T Ma, A Risteski
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017
342017
Algorithms and matching lower bounds for approximately-convex optimization
A Risteski, Y Li
Advances in Neural Information Processing Systems 29, 4745-4753, 2016
332016
Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates
Y Li, Y Liang, A Risteski
Advances in Neural Information Processing Systems 29, 4987-4995, 2016
332016
Algorithms and matching lower bounds for approximately-convex optimization
A Risteski, Y Li
Advances in Neural Information Processing Systems 29, 4745-4753, 2016
332016
Recovery guarantee of non-negative matrix factorization via alternating updates
Y Li, Y Liang, A Risteski
Advances in Neural Information Processing Systems, 4987-4995, 2016
332016
Recovery guarantee of weighted low-rank approximation via alternating minimization
Y Li, Y Liang, A Risteski
International Conference on Machine Learning, 2358-2367, 2016
322016
Empirical study of the benefits of overparameterization in learning latent variable models
RD Buhai, Y Halpern, Y Kim, A Risteski, D Sontag
International Conference on Machine Learning, 1211-1219, 2020
28*2020
Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective
V Jain, F Koehler, A Risteski
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019
282019
The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure
F Koehler, A Risteski
International Conference on Learning Representations, 2018
23*2018
On some provably correct cases of variational inference for topic models
P Awasthi, A Risteski
Advances in Neural Information Processing Systems, 2098-2106, 2015
232015
An online learning approach to interpolation and extrapolation in domain generalization
E Rosenfeld, P Ravikumar, A Risteski
International Conference on Artificial Intelligence and Statistics, 2641-2657, 2022
222022
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Artikkelit 1–20