Navin Goyal

According to our database1, Navin Goyal authored at least 62 papers between 2003 and 2023.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

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Bibliography

2023
Guiding Language Models of Code with Global Context using Monitors.
CoRR, 2023

In-Context Learning through the Bayesian Prism.
CoRR, 2023

A Theory of Emergent In-Context Learning as Implicit Structure Induction.
CoRR, 2023

Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Towards a Mathematics Formalisation Assistant using Large Language Models.
CoRR, 2022

Robust identifiability in linear structural equation models of causal inference.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Learning and Generalization in Overparameterized Normalizing Flows.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Revisiting the Compositional Generalization Abilities of Neural Sequence Models.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

2021
Analyzing the Nuances of Transformers' Polynomial Simplification Abilities.
CoRR, 2021

Learning and Generalization in RNNs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Are NLP Models really able to Solve Simple Math Word Problems?
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

2020
On the Ability of Self-Attention Networks to Recognize Counter Languages.
CoRR, 2020

Effect of Activation Functions on the Training of Overparametrized Neural Nets.
Proceedings of the 8th International Conference on Learning Representations, 2020

On the Ability and Limitations of Transformers to Recognize Formal Languages.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

On the Computational Power of Transformers and Its Implications in Sequence Modeling.
Proceedings of the 24th Conference on Computational Natural Language Learning, 2020

On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019
Better analysis of greedy binary search tree on decomposable sequences.
Theor. Comput. Sci., 2019

Non-Gaussianity of Stochastic Gradient Noise.
CoRR, 2019

Stability of Linear Structural Equation Models of Causal Inference.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Non-Gaussian component analysis using entropy methods.
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature.
Proceedings of the Conference on Learning Theory, 2019

2018
Depth separation and weight-width trade-offs for sigmoidal neural networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Near-Optimal Regret Bounds for Thompson Sampling.
J. ACM, 2017

Heavy-Tailed Analogues of the Covariance Matrix for ICA.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
On Computing Maximal Independent Sets of Hypergraphs in Parallel.
ACM Trans. Parallel Comput., 2016

Non-negative Matrix Factorization under Heavy Noise.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Query Complexity of Sampling and Small Geometric Partitions.
Comb. Probab. Comput., 2015

Heavy-Tailed Independent Component Analysis.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

2014
Lower Bounds for the Average and Smoothed Number of Pareto-Optima.
Theory Comput., 2014

Expanders via Random Spanning Trees.
SIAM J. Comput., 2014

Fourier PCA and robust tensor decomposition.
Proceedings of the Symposium on Theory of Computing, 2014

Annotations for Sparse Data Streams.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Deterministic Algorithms for the Lovász Local Lemma.
SIAM J. Comput., 2013

The VPN Conjecture Is True.
J. ACM, 2013

Fourier PCA.
CoRR, 2013

Ad impression forecasting for sponsored search.
Proceedings of the 22nd International World Wide Web Conference, 2013

Thompson Sampling for Contextual Bandits with Linear Payoffs.
Proceedings of the 30th International Conference on Machine Learning, 2013

Efficient Learning of Simplices.
Proceedings of the COLT 2013, 2013

Further Optimal Regret Bounds for Thompson Sampling.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Analysis of Thompson Sampling for the Multi-armed Bandit Problem.
Proceedings of the COLT 2012, 2012

Efficient learning of simplices
CoRR, 2012

Lower Bounds for the Average and Smoothed Number of Pareto Optima.
Proceedings of the IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, 2012

2011
On Dynamic Optimality for Binary Search Trees
CoRR, 2011

Dynamic vs. Oblivious Routing in Network Design.
Algorithmica, 2011

2010
Rounds vs. Queries Tradeoff in Noisy Computation.
Theory Comput., 2010

Satisfiability Thresholds for k-CNF Formula with Bounded Variable Intersections
CoRR, 2010

Enhanced flux balance analysis to model metabolic networks.
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology, 2010

2009
Expanders via random spanning trees.
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

Learning Convex Bodies is Hard.
Proceedings of the COLT 2009, 2009

2008
Lower Bounds for the Noisy Broadcast Problem.
SIAM J. Comput., 2008

Disorder inequality: a combinatorial approach to nearest neighbor search.
Proceedings of the International Conference on Web Search and Web Data Mining, 2008

2007
An Algorithmic Approach to the Identification of Rigid Domains in Proteins.
Algorithmica, 2007

2006
The Graham-Knowlton Problem Revisited.
Theory Comput. Syst., 2006

An Efficient Approximation Algorithm for Point Pattern Matching Under Noise.
Proceedings of the LATIN 2006: Theoretical Informatics, 2006

Lower bounds for circuits with MOD_m gates.
Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), 2006

2005
A parallel search game.
Random Struct. Algorithms, 2005

Rounds vs queries trade-off in noisy computation.
Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2005

2004
A Combinatorial Shape Matching Algorithm for Rigid Protein Docking.
Proceedings of the Combinatorial Pattern Matching, 15th Annual Symposium, 2004

2003
Optimal Bandwidth Reservation Schedule in Cellular Network.
Proceedings of the Proceedings IEEE INFOCOM 2003, The 22nd Annual Joint Conference of the IEEE Computer and Communications Societies, San Franciso, CA, USA, March 30, 2003

Optimal Separation of EROW and CROWPRAMs.
Proceedings of the 18th Annual IEEE Conference on Computational Complexity (Complexity 2003), 2003


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