Some Recent Papers

(Click here for all papers)

Average-Case Lower Bounds for Learning Sparse Mixtures, Robust Estimation and Semirandom Adversaries
The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs
Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness
Universality of Computational Lower Bounds for Submatrix Detection
Stein's Method for Stationary Distributions of Markov Chains and Application to Ising Models
Learning Restricted Boltzmann Machines via Influence Maximization
Learning Tree-structured Ising Models in Order to Make Predictions
Information Storage in the Stochastic Ising Model at Zero Temperature
Optimal Single Sample Tests for Structured versus Unstructured Network Data
Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure
Regret Bounds and Regimes of Optimality for Item-item and User-user Collaborative Filtering

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