Internal Program Activities Breadcrumb Home Programs & Events Internal Program Activities Upcoming Past View Events by Program - All - View Events by Program No Internal Activities yet. View Events by Program - All -Quantum Research PodModern Paradigms in GeneralizationSublinear AlgorithmsError-Correcting Codes: Theory and PracticeLogic and Algorithms in Database Theory and AIData Structures and Optimization for Fast AlgorithmsAnalysis and TCS: New FrontiersSummer Cluster on Quantum ComputingMeta-ComplexityExtended Reunion: SatisfiabilityData-Driven Decision ProcessesGraph Limits and Processes on Networks: From Epidemics to MisinformationSummer Cluster: AI and HumanitySummer Cluster: Interpretable Machine LearningComputational Innovation and Data-Driven BiologySummer Cluster: Deep Learning TheoryCausalityLearning and GamesGeometric Methods in Optimization and SamplingComputational Complexity of Statistical InferenceTheoretical Foundations of Computer SystemsSatisfiability: Theory, Practice, and BeyondTheory of Reinforcement LearningProbability, Geometry, and Computation in High DimensionsLattices: Algorithms, Complexity, and CryptographyThe Quantum Wave in ComputingProofs, Consensus, and Decentralizing SocietyOnline and Matching-Based Market DesignSummer Cluster: Error-Correcting Codes and High-Dimensional ExpansionFoundations of Deep LearningData Privacy: Foundations and ApplicationsGeometry of PolynomialsFoundations of Data ScienceLower Bounds in Computational ComplexityThe Brain and ComputationReal-Time Decision MakingBridging Continuous and Discrete OptimizationFoundations of Machine LearningPseudorandomnessLogical Structures in ComputationAlgorithms and UncertaintyAlgorithmic Challenges in GenomicsCounting Complexity and Phase TransitionsFine-Grained Complexity and Algorithm DesignEconomics and ComputationCryptographyInformation TheoryAlgorithmic Spectral Graph TheoryAlgorithms and Complexity in Algebraic GeometryEvolutionary Biology and the Theory of ComputingQuantum Hamiltonian ComplexityReal Analysis in Computer ScienceTheoretical Foundations of Big Data Analysis View Events by Program How To Beat Empirical Risk Minimization How To Beat Empirical Risk Minimization Foundations of Deep Learning Ali Rahimi Some of my favorite open problems on expanders (and related objects) Some of my favorite open problems on expanders (and related objects) Summer Cluster: Error-Correcting Codes and High-Dimensional Expansion Avi Wigderson (IAS) Fourier Analysis on Exotic Domains Fourier Analysis on Exotic Domains Summer Cluster: Error-Correcting Codes and High-Dimensional Expansion Yuval Filmus Tutorial on Lifted Codes Tutorial on Lifted Codes Summer Cluster: Error-Correcting Codes and High-Dimensional Expansion Prahladh Harsha High-Dimensional Expanders from Expanders High-Dimensional Expanders from Expanders Summer Cluster: Error-Correcting Codes and High-Dimensional Expansion Siqi Liu Approximating CSPs on HDXs, and applications to codes Approximating CSPs on HDXs, and applications to codes Summer Cluster: Error-Correcting Codes and High-Dimensional Expansion Madhur Tulsiani Robust Bi-Tempered Logistic Loss Based on Bregman Divergences Robust Bi-Tempered Logistic Loss Based on Bregman Divergences Foundations of Deep Learning Manfred K. Warmuth Private Deep Learning Private Deep Learning Foundations of Deep Learning Shafi Goldwasser Graphs which are expanders both locally and globally Graphs which are expanders both locally and globally Summer Cluster: Error-Correcting Codes and High-Dimensional Expansion Michael Chapman From local to robust testing via high-dimensional expansion From local to robust testing via high-dimensional expansion Summer Cluster: Error-Correcting Codes and High-Dimensional Expansion Noga Ron Zewi Pagination First page First Previous page Previous Page 89 Page 90 Current page 91 Page 92 Page 93 Next page Next Last page Last
