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 CCSI Reading Group: Cryptography and Learning CCSI Reading Group: Cryptography and Learning Computational Complexity of Statistical Inference CCSI/GMOS Student Seminar CCSI/GMOS Student Seminar Geometric Methods in Optimization and Sampling GMOS Working Group: Manifolds and Symmetry GMOS Working Group: Manifolds and Symmetry Geometric Methods in Optimization and Sampling GMOS Working Group: Complexity of Sampling GMOS Working Group: Complexity of Sampling Geometric Methods in Optimization and Sampling GMOS Working Group: Sampling with Kernelized Wasserstein Gradient Flows GMOS Working Group: Sampling with Kernelized Wasserstein Gradient Flows Geometric Methods in Optimization and Sampling GMOS Working Group: Optimal Transport GMOS Working Group: Optimal Transport Geometric Methods in Optimization and Sampling GMOS Working Group: Consensus Based Optimization GMOS Working Group: Consensus Based Optimization Geometric Methods in Optimization and Sampling CCSI Reading Group: Statistical Physics and Computation CCSI Reading Group: Statistical Physics and Computation Computational Complexity of Statistical Inference CCSI Reading Group: Reductions CCSI Reading Group: Reductions Computational Complexity of Statistical Inference GMOS Weekly Seminar - Convergence of Online SGD Under Infinite Noise Variance, and Non-Convexity GMOS Weekly Seminar - Convergence of Online SGD Under Infinite Noise Variance, and Non-Convexity Geometric Methods in Optimization and Sampling Murat A. Erdogdu (University of Toronto) Pagination First page First Previous page Previous Page 63 Page 64 Current page 65 Page 66 Page 67 Next page Next Last page Last
