Guy Bresler
23 papers · 2014–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (11) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (4) π Cross-Pollinator (14)
π
Cross-Pollinator
(14)
π
Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(31)
π§¬
Topic Evolution
π
Keyword Champion
(6)
π
Century Club
(23)
ποΈ
Keyword Collector
(95)
β‘
Prolific Year
(5)
π₯
Unstoppable
(8)
π
Trend Setter
Conferences
COLT (12)
NIPS (9)
ALT (1)
JMLR (1)
Top co-authors
Keywords
planted clique
(6)
graphical model
(4)
hypothesis testing
(3)
average-case reduction
(3)
parameter estimation
(2)
ising model
(2)
markov random field
(2)
sparse principal component analysis
(2)
computational lower bound
(2)
sparse pca
(2)
tensor pca
(2)
sample complexity
(1)
probabilistic modeling
(1)
expectation maximization
(1)
collaborative filtering
(1)
online learning
(1)
active learning
(1)
structure learning
(1)
hierarchical learning
(1)
stochastic gradient descent
(1)
Papers
Computational Equivalence of Spiked Covariance and Spiked Wigner Models via Gram-Schmidt Perturbation
COLT 2025
Computationally efficient reductions between some statistical models
ALT 2025
Partial and Exact Recovery of a Random Hypergraph from its Graph Projection
COLT 2025
Detection of $L_β$ Geometry in Random Geometric Graphs: Suboptimality of Triangles and Cluster Expansion
COLT 2024
Thresholds for Reconstruction of Random Hypergraphs From Graph Projections
COLT 2024
Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique
COLT 2023
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures
JMLR 2022
Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent
COLT 2021
The staircase property: How hierarchical structure can guide deep learning
NIPS 2021
Reducibility and Statistical-Computational Gaps from Secret Leakage
COLT 2020
A Corrective View of Neural Networks: Representation, Memorization and Learning
COLT 2020
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
NIPS 2020
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
NIPS 2020
Learning Restricted Boltzmann Machines with Sparse Latent Variables
NIPS 2020
Sample Efficient Active Learning of Causal Trees
NIPS 2019
Universality of Computational Lower Bounds for Submatrix Detection
COLT 2019
Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness
COLT 2019
Optimal Single Sample Tests for Structured versus Unstructured Network Data
COLT 2018
Sparse PCA from Sparse Linear Regression
NIPS 2018
Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure
COLT 2018
Hardness of parameter estimation in graphical models
NIPS 2014
A Latent Source Model for Online Collaborative Filtering
NIPS 2014
Structure learning of antiferromagnetic Ising models
NIPS 2014