Search for tag: "gradient"

AML: Optimisation - Stochastic Gradient Descent

Applied Machine Learning - INFR11211 AML: Optimisation - Stochastic Gradient Descent Part 3/3

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AML: Optimisation - Gradient Descent

Applied Machine Learning - INFR11211 AML: Optimisation - Gradient Descent Part 2/3

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From  Siddharth N 3 likes 620 plays 0  

AML: Optimisation - ML Optimisation

Applied Machine Learning - INFR11211 AML: Optimisation - ML Optimisation Part 1/3

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From  Siddharth N 2 likes 619 plays 0  

Sharp subelliptic estimates via an uncertainty principle - Gian Maria Dall'Ara

Fourier Analysis @ 200 Sharp subelliptic estimates via an uncertainty principle Gian Maria Dall'Ara, Scuola Normale Superiore (Pisa) 30 June 2022

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From  Iain Cms 0 likes 37 plays 0  

Phase Behaviour, Biased Ensembles and Optimal Control of Active Particles - Mike Cates

From Individual to Collective Behaviour in Biological and Robotic Systems Phase Behaviour, Biased Ensembles and Optimal Control of Active Particles DAMTP, University of Cambridge Mike Cates

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Active Brownian Particles and chemotaxis - Oscar de Wit

From Individual to Collective Behaviour in Biological and Robotic Systems Active Brownian Particles and chemotaxis University of Cambridge Oscar de Wit

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Flocks, mills, and platoons: from ad-hoc design to optimality-based formulation - Dante Kalise

From Individual to Collective Behaviour in Biological and Robotic Systems Flocks, mills, and platoons: from ad-hoc design to optimality-based formulation Imperial College London Dante Kalise

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Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs - Zhou Fan

Structural Breaks and Shape Constraints Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs Zhou Fan (Yale University) 17 May 2022

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Immersed Method with Metric Based Anisotropic Meh Adaptation for Computational Multiphase Flow Dynamics - Thierry Coupez

Adaptive Moving and Anisotropic Meshes for the Numerical Approximation of PDEs Immersed Method with Metric Based Anisotropic Meh Adaptation for Computational Multiphase Flow Dynamics Thierry…

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One World SNIPS: Lukasz Szpruch

One World Virtual Seminar Series - Stochastic Numerics and Inverse Problems, 02 February 2022 Lukasz Szpruch (University of Edinburgh / Alan Turing Institute) From the theory of (stochastic)…

From  Simon Kershaw 0 likes 53 plays 0  

Stefano Modena - Thursday 11 November

08 Nov- 12 Nov 2021ICMS hosted the Convex Integration and Nonlinear Partial Differential Equations workshopNon-uniqueness for the transport equation with Sobolev vector fields Stefano Modena (TU -…

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Angkana Ruland - Monday 8 November

08 Nov- 12 Nov 2021 ICMS hosted the Convex Integration and Nonlinear Partial Differential Equations workshop Rigidity and Flexibility in the Modelling of Shape-Memory Alloys Angkana Ruland…

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From  Simon Kershaw 0 likes 86 plays 0  

Anis Hamadouche Presentation - SSPD 2021

Presented at the Sensor Signal Processing for Defence Conference (SSPD) 2021Presentation: "Approximate Proximal-Gradient Methods" Speaker: Anis Hamadouche, Heriot-Watt…

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Stefan Perko Student Talks

30 Aug- 03 Sept 2021 ICMS hosted the European Summer School in Financial Mathematics 14th Edition Approximating stochastic gradient descent with diffusions: error expansions and impact of learning…

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From  Greg McCracken 0 likes 48 plays 0  

James Foster - Neural stochastic differential equations for time series modelling

30 Aug- 03 Sept 2021 ICMS hosted the European Summer School in Financial Mathematics 14th Ediition Neural stochastic differential equations for time series modelling James Foster (University…

From  Greg McCracken 0 likes 37 plays 0  

Bayesian Extremes: Rishikesh Yadav

This talk has been automatically captioned. You can remove these by pressing CC on the video toolbar. Name: Rishikesh Yadav Talk Title: A flexible Bayesian framework for modeling extreme…

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From  Belle Taylor 0 likes 28 plays 0