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Vladimir Vapnik

INSTITUTE for COMPUTATIONAL and BIOLOGICAL LEARNING (ICBL)
A Priori Knowledge from Non-Examples
United States Patent 19 11 Patent Number: 5,640,492 Cortes Et Al
On the State of the Art in Machine Learning: a Personal Review
UNIVERSITY of CALIFORNIA Los Angeles Data-Driven Learning Of
Accelerating Text-As-Data Research in Computational Social Science
Teaching with IMPACT
April 8-11, 2019 the 2019 Franklin Institute Laureates the 2019 Franklin Institute AWARDS CONVOCATION APRIL 8–11, 2019
On-Device Machine Learning: an Algorithms and Learning Theory Perspective
Lipics-ESA-2020-38.Pdf (0.8
Arxiv:2105.01867V1 [Cs.LG] 5 May 2021
Ieee-Level Awards
Session II – Unit I – Fundamentals
An Experimental and Theoretical Comparison of Model Selection Methods*
Support Vector Machines
Machine Learning Testing: Survey, Landscapes and Horizons
Algorithms and Hardness for Linear Algebra on Geometric Graphs
Algorithms and Hardness for Linear Algebra on Geometric Graphs

Top View

Introduction to Support Vector Machines
Measures of Complexity Vladimir Vovk • Harris Papadopoulos Alexander Gammerman Editors
Efficient Active Learning of Sparse Halfspaces with Arbitrary Bounded
A Stochastic Algorithm for Feature Selection in Pattern Recognition
Document Provisoire
Contents U U U
A Framework for Structural Risk Minimisation
Full Book As
Support-Vector Networks
Two Computer Science Professors Win Sloan Fellowships
Point Location and Active Learning: Learning Halfspaces Almost Optimally
Supervised Classification of Microtubule Ends
Inner Product Spaces for Bayesian Networks
Columbia Computer Science Faculty in the National Academies
Attachment 2: Profile of the Group B Recipient of the 2013 C&C Prize
Feature Extraction for Side-Channel Attacks Eleonora Cagli
Support Vector Machines
Association for Computing Machinery 2 Penn Plaza, Suite 701, New York

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