Search for tag: "gradient"

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42:42 Tree-Projected Gradient Descent for Estimating… Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs - Zhou Fan	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 icms tree graph star edge sparsity theta kind gradient subspace loss idea algorithm projection space step question problem factor kinds edges From Frances Allen 0 likes 5 plays 0 Licence Type All rights reserved Language English Date Created May 19th, 2022
47:03 Immersed Method with Metric Based Anisotropic Meh… Immersed Method with Metric Based Anisotropic Meh Adaptation for Computational Multiphase Flow Dynamics - Thierry Coupez	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… mesh pressure 3d edge fact ash gradient function bit metric amount solution direction jump visa size sickness equation stokes cylinder From Frances Allen 0 likes 8 plays 0 Licence Type All rights reserved Language English Date Created May 11th, 2022
51:45 One World SNIPS: Lukasz Szpruch One World SNIPS: Lukasz Szpruch	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)… stochastic numerics one world numerics control function measure gradient problem equation measures network model learning dynamics parameters guy problems layer sigma distribution cost flow functions From Simon Kershaw 0 likes 30 plays 0 Licence Type All rights reserved
24:08 Stefano Modena - Thursday 11 November Stefano Modena - Thursday 11 November	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 -… icms convex integration pdes vector uniqueness field class equation space density infinity solutions question gradient fields condition lp cities solution transport incompressibility divergence talk From Simon Kershaw 0 likes 18 plays 0 Licence Type All rights reserved Language English Date Created November 11th, 2021
42:18 Angkana Ruland - Monday 8 November Angkana Ruland - Monday 8 November	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… ruland convex integration nonlinear solutions problem differential energy solution fact boundary inclusion phase flexibility model transformations regularity convex matrices picture gradient material structures matrix From Simon Kershaw 0 likes 46 plays 0 Licence Type All rights reserved
09:47 Anis Hamadouche Presentation - SSPD 2021 Anis Hamadouche Presentation - SSPD 2021	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… sspd 2021 error bounds rate convergence errors table analysis approximations precision algorithm function gradient bound assumptions problems optimization application step vector dimensionality From Joe Burchell 0 likes 21 plays 0 Licence Type All rights reserved Language English Date Created September 15th, 2021
09:13 Stefan Perko Student Talks Stefan Perko Student Talks	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… icms perko stochastic gradient approximation gradient diffusion rate flow times sgd learning result age step phi sme loss term difference expectation sigma coefficient x. From OLLIE Quinn 0 likes 18 plays 0 Licence Type All rights reserved Date Created September 2nd, 2021
31:09 James Foster - Neural stochastic differential… James Foster - Neural stochastic differential equations for time series modelling	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 of… series modelling foster neural stochastic sd function loss distance question network networks model samples motion models series things discriminator gradient generator approach linear train solution From OLLIE Quinn 0 likes 16 plays 0 Licence Type All rights reserved
19:35 Bayesian Extremes: Rishikesh Yadav Bayesian Extremes: Rishikesh Yadav	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 spatial… eva model models distribution gradient dependence beta vector alpha parameters tail mcmc scale copula independence mixture sites size process x2 diamonds From Belle Taylor 0 likes 21 plays 0 Publisher Centre for Statistics Licence Type All rights reserved Language English Date Created June 30th, 2021
03:06 Clement Dombry EVA Talk Preview Clement Dombry EVA Talk Preview	Clement Dombry EVA Talk Preview This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Clement Dombry Talk Title: Gradient boosting for extreme quantile regression Abstract: Extreme quantile… eva icms theory solution gradient boosting extremes quantiles regression data models range values methods hyperparameters dimension curse estimation parameters covariates threshold exceedances distribution power alpha observations talk uva netherlands precipitation From Anna Munro 0 likes 39 plays 0 Licence Type All rights reserved Language English
02:58 Rishikesh Yadav EVA Talk Preview Rishikesh Yadav EVA Talk Preview	Rishikesh Yadav EVA Talk Preview This talk has captions. You can remove these by pressing CC on the video toolbar. Name: Rishikesh Yadav Talk Title: A flexible Bayesian framework for modeling extreme spatial threshold exceedances… eva icms theory solution models flexible frameworks modelling extremes spatial mixtures fields random model beta dependence computation structure parameter limit parameters respect iid x2 field update constructs diamond techniques mcmc gradient types From Anna Munro 0 likes 10 plays 0 Licence Type All rights reserved Language English
58:34 UK-APASI in Mathematical Sciences: Fred Vermolen UK-APASI in Mathematical Sciences: Fred Vermolen	UK-APASI in Mathematical Sciences: Fred Vermolen Subtitles will be added soon. Fred Vermolen, Finite element method for PDEs: Part II functions phi solution times gradient function thing basis approximation error omega linear boundary points problem idea equations cetera formulation triangle From Liam Holligan 0 likes 22 plays 0 Publisher Liam Holligan Licence Type All rights reserved Language English Date Created April 30th, 2021
48:18 UK-APASI in Mathematical Sciences:Fred Vermolen UK-APASI in Mathematical Sciences:Fred Vermolen	UK-APASI in Mathematical Sciences:Fred Vermolen Subtitles will be added soon. Fred Vermolen, Finite element method for PDEs: Part I omega phi function times boundary domain methods divergence gradient method formulation equation solution theorem vector derivatives differentiation problem laplacian difference From Liam Holligan 0 likes 18 plays 0 Publisher Liam Holligan Licence Type All rights reserved Language English Date Created April 30th, 2021
45:34 One World Virtual Seminar Series - Stochastic… One World Virtual Seminar Series - Stochastic Numerics and Inverse Problems: Monika Eisenmann	One World Virtual Seminar Series - Stochastic Numerics and Inverse Problems: Monika Eisenmann One World Virtual Seminar Series - Stochastic Numerics and Inverse Problems: Monika Eisenmann (Lund University) Sub-linear convergence of stochastic optimization methods in Hilbert space Automatic… icms stochastic numerics hilbert space step method gradient size euler scheme problem convergence function setting point points flow batch equation steps error sequence methods result From Jane Walker 0 likes 117 plays 0 Publisher Diane Hoberry Licence Type All rights reserved Language English Date Created March 31st, 2021
20:43 Modelling of acoustic wave propagation in… Modelling of acoustic wave propagation in realistic ocean environment	Modelling of acoustic wave propagation in realistic ocean environment UDRC Themed Meeting on Signal Processing in the Underwater Environment by Sourav Sahoo, National Oceanography Centre (NOC) udrc signal processing velocity structure source column water difference 3d metre amplitudes 2d kilometre model amplitude kind reduction density signal sea methods gradient From Maddy McBeath 0 likes 8 plays 0 Licence Type All rights reserved The University of Edinburgh Date Created March 30th, 2021
01:01:20 8 March 2021 - Carola-Bibiane Schönlieb… 8 March 2021 - Carola-Bibiane Schönlieb (University of Cambridge) - Structure-preserving deep learning	8 March 2021 - Carola-Bibiane Schönlieb (University of Cambridge) - Structure-preserving deep learning 8 March 2021 Carola-Bibiane Schönlieb (University of Cambridge) - Structure-preserving deep learning Abstract: Over the past few years, deep learning has risen to the foreground as a topic of… one world numerical analysis owna network networks kind function learning ode input output layers problem problems gradient thing layer linear image training analysis instance continuum From OLLIE Quinn 0 likes 111 plays 0 Licence Type All rights reserved Language English Date Created March 8th, 2021

Search for tag: "gradient"

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