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 Determinantal representations of hyperbolic polynomials Determinantal representations of hyperbolic polynomials Geometry of Polynomials Daniel Plaumann (TU Dortmund) Problems in Matrix Variables: A Taste of Noncommutative (Convex) Algebraic Geometry *starts at 10:15 a.m. sharp* Problems in Matrix Variables: A Taste of Noncommutative (Convex) Algebraic Geometry *starts at 10:15 a.m. sharp* Geometry of Polynomials Bill Helton (UC San Diego) Privacy and Statistical Inference for Social Science Data (Data Privacy Reading Group) Privacy and Statistical Inference for Social Science Data (Data Privacy Reading Group) Data Privacy: Foundations and Applications Optimality and large-scale learning under local privacy Optimality and large-scale learning under local privacy Data Privacy: Foundations and Applications John Duchi (Stanford) Colouring locally sparse graphs via the hard-core model Colouring locally sparse graphs via the hard-core model Geometry of Polynomials Ewan Davies, Simons Institute Ground states and Hyperuniformity properties for models of interacting gas. Ground states and Hyperuniformity properties for models of interacting gas. Geometry of Polynomials Shirshendu Ganguly, UC Berkeley Privacy and Statistical Inference for Social Science Data (Data Privacy Reading Group) Privacy and Statistical Inference for Social Science Data (Data Privacy Reading Group) Data Privacy: Foundations and Applications Google Talks Field Trip Google Talks Field Trip Data Privacy: Foundations and Applications Next mini course: McMullen’s polytope algebra Next mini course: McMullen’s polytope algebra Geometry of Polynomials Raman Sanyal Differentially Private Learning of Geometric Concepts Differentially Private Learning of Geometric Concepts Data Privacy: Foundations and Applications Uri Stemmer (Ben Gurion University) Pagination First page First Previous page Previous Page 91 Page 92 Current page 93 Page 94 Page 95 Next page Next Last page Last
