Andrej Risteski
According to our database1,
Andrej Risteski
authored at least 61 papers
between 2012 and 2023.
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Bibliography
2023
Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization.
CoRR, 2023
Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Markov Chains.
CoRR, 2023
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation.
CoRR, 2023
Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization.
CoRR, 2022
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flows.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the Algorithmic Learning Theory, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021
2020
Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
CoRR, 2019
Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective.
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019
The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure.
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the Conference on Learning Theory, 2019
2018
Trans. Assoc. Comput. Linguistics, 2018
Simulated Tempering Langevin Monte Carlo II: An Improved Proof using Soft Markov Chain Decomposition.
CoRR, 2018
Representational Power of ReLU Networks and Polynomial Kernels: Beyond Worst-Case Analysis.
CoRR, 2018
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017
Proceedings of the 30th Conference on Learning Theory, 2017
2016
Trans. Assoc. Comput. Linguistics, 2016
Proceedings of the 15th Scandinavian Symposium and Workshops on Algorithm Theory, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods.
Proceedings of the 29th Conference on Learning Theory, 2016
2015
Random Walks on Context Spaces: Towards an Explanation of the Mysteries of Semantic Word Embeddings.
CoRR, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of The 28th Conference on Learning Theory, 2015
2014
2012
Proceedings of the 24th Canadian Conference on Computational Geometry, 2012