S.v.n. Vishwanathan
18 papers · 2005–2019 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (44) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
π±
Topic Pioneer
π
Keyword Trendsetter Combo
(9)
π
Keyword Champion
π§
Keyword Pioneer
π
Trend Setter
β‘
Prolific Year Β· Productive
ποΈ
Keyword Collector
(106)
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
π
Conference Pioneer
Top co-authors
Research topics
Machine Learning
(16)
Core Methods
(15)
Mathematics & Optimization
(13)
Optimization & Theory
(11)
Optimization
(10)
Learning Types
(5)
Mathematics
(4)
Artificial Intelligence
(3)
Deep Learning
(3)
Bayesian & Probabilistic Β· Machine Learning
(3)
Computer Science
(2)
Foundations
(2)
Healthcare & Medicine
(1)
Architectures
(1)
Bayesian & Probabilistic Β· Artificial Intelligence
(1)
Keywords
kernel methods
(5)
graph kernel
(4)
convex optimization
(3)
stochastic optimization
(3)
reproducing kernel hilbert space
(3)
support vector machine
(3)
smoothing technique
(2)
regularized risk minimization
(2)
classification
(2)
variational inference
(2)
lower bound
(2)
label noise
(2)
random walk
(2)
cutting plane method
(2)
hinge loss
(2)
convergence analysis
(2)
logistic regression
(1)
bayesian inference
(1)
approximate inference
(1)
feature extraction
(1)
Papers
Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models
AISTATS 2019
A Structural Smoothing Framework For Robust Graph Comparison
NeurIPS 2015
Open Problem: Lower bounds for Boosting with Hadamard Matrices
COLT 2013
Smoothing Multivariate Performance Measures
JMLR 2012
t-divergence Based Approximate Inference
NeurIPS 2011
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
JMLR 2010
Graph Kernels
JMLR 2010
Lower Bounds on Rate of Convergence of Cutting Plane Methods
NeurIPS 2010
Multiple Kernel Learning and the SMO Algorithm
NeurIPS 2010
Multitask Learning without Label Correspondences
NeurIPS 2010
t-logistic regression
NeurIPS 2010
Hash Kernels for Structured Data
JMLR 2009
Bundle Methods for Machine Learning
NeurIPS 2007
Semi-Markov Models for Sequence Segmentation
EMNLP 2007
Fast Computation of Graph Kernels
NeurIPS 2006
Fast Iterative Kernel PCA
NeurIPS 2006
implicit Online Learning with Kernels
NeurIPS 2006
Variable Metric Stochastic Approximation Theory
AISTATS 2005