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Home > Applied Mathematics

Partial Permutation Synchronization via Cycle-Edge Message Passing [1]

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Multi-Reference Alignment In High Dimensions [2]

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Dual Principal Component Pursuit [3]

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A Fast, Stable QR Algorithm for the Diagonalization of Colleague Matrices [4]

  • Read more about A Fast, Stable QR Algorithm for the Diagonalization of Colleague Matrices [4]

New Methods for Low-Rank Matrix Denoising [5]

  • Read more about New Methods for Low-Rank Matrix Denoising [5]

The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning [6]

  • Read more about The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning [6]

Fast & Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems [7]

  • Read more about Fast & Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems [7]

Kernel two-sample test: on manifold data and by neural tangent kernel [8]

  • Read more about Kernel two-sample test: on manifold data and by neural tangent kernel [8]

Manifold learning with non-Euclidean norms, and orbit recovery [9]

  • Read more about Manifold learning with non-Euclidean norms, and orbit recovery [9]

How to apply manifold learning and random matrix theory to study complicated time series? [10]

  • Read more about How to apply manifold learning and random matrix theory to study complicated time series? [10]
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[1] https://calendar.math.yale.edu/event/partial-permutation-synchronization-cycle-edge-message-passing [2] https://calendar.math.yale.edu/event/multi-reference-alignment-high-dimensions [3] https://calendar.math.yale.edu/event/dual-principal-component-pursuit [4] https://calendar.math.yale.edu/event/fast-stable-qr-algorithm-diagonalization-colleague-matrices [5] https://calendar.math.yale.edu/event/new-methods-low-rank-matrix-denoising [6] https://calendar.math.yale.edu/event/polyak-lojasiewicz-condition-framework-over-parameterized-optimization-and-its-application [7] https://calendar.math.yale.edu/event/fast-accurate-randomized-algorithms-linear-systems-and-eigenvalue-problems [8] https://calendar.math.yale.edu/event/kernel-two-sample-test-manifold-data-and-neural-tangent-kernel [9] https://calendar.math.yale.edu/event/manifold-learning-non-euclidean-norms-and-orbit-recovery [10] https://calendar.math.yale.edu/event/how-apply-manifold-learning-and-random-matrix-theory-study-complicated-time-series [11] https://calendar.math.yale.edu/seminars/applied-mathematics [12] https://calendar.math.yale.edu/seminars/applied-mathematics?page=3 [13] https://calendar.math.yale.edu/seminars/applied-mathematics?page=1 [14] https://calendar.math.yale.edu/seminars/applied-mathematics?page=2 [15] https://calendar.math.yale.edu/seminars/applied-mathematics?page=5 [16] https://calendar.math.yale.edu/seminars/applied-mathematics?page=6 [17] https://calendar.math.yale.edu/seminars/applied-mathematics?page=7 [18] https://calendar.math.yale.edu/seminars/applied-mathematics?page=8 [19] https://calendar.math.yale.edu/seminars/applied-mathematics?page=28