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Explore advanced tensor decomposition techniques and their applications in latent variable models, phylogenetics, mixture models, and orbit retrieval with MIT's Ankur Moitra.
Explore tensor geometry and its applications in physical and data sciences through a gentle introduction, emphasizing how geometric perspectives advance practical implementations.
Explore tensor decompositions and their applications in latent variable models, focusing on Jennrich's algorithm and its use in various fields like phylogenetics and mixture models.
Explore the geometric perspective of tensors, their applications, and how this viewpoint enhances understanding in various fields. Gentle introduction suitable for beginners.
Explore stabilizer formalism and quantum error correction using tensor methods. Learn about many-body systems, error correction challenges, and connections to finite symplectic geometries.
Explore low rank tensor methods for analyzing high-dimensional data in various fields. Learn about recent progress, challenges, and applications in extracting information from multilinear arrays.
Explore the integration of machine learning and discrete optimization to enhance problem-solving in real-world scenarios, focusing on decision-focused learning and tailored solution strategies.
Explore advanced techniques in semidefinite programming for combinatorial optimization, focusing on fast and differentiable methods presented by Carnegie Mellon expert Zico Kolter.
Explores connections between sparse linear programming and neural networks, focusing on overparametrized learning and sparse inference from computational perspectives.
Explore conditional gradient methods for structured optimization in machine learning, covering applications in traditional and deep learning, with a focus on incorporating polyhedral structures into solutions.
Explores a chain rule for quantum relative entropy, its implications for quantum statistics, and the comparison of adaptive vs non-adaptive strategies in quantum channel discrimination.
Explores semidefinite programming for quantum correlations, improving approximation algorithms for two-player free games with quantum assistance using entropy inequalities and de Finetti theorems.
Explore the classification of small fusion categories, including recent results on odd-dimensional modular and fusion categories. Learn about different interpretations of "small" in this context.
Exploration of weak quasi-Hopf algebras in relation to Verlinde fusion categories, discussing unitarity, quantum groups, and potential applications to Kazhdan-Lusztig-Finkelberg theorem.
Explore classification of outer actions of amenable groups on von Neumann algebras, focusing on II_1 factors. Covers Ocneanu's uniqueness theorem and Popa's work on 2-cohomology vanishing.
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