Ingo Steinwart
28 papers · 2001–2024 · 6 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Conference Polyglot (6) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (15) π Academic Marathon (23)
πΊοΈ
Taxonomy Completionist
(15)
π
Cross-Pollinator
(14)
π§
Keyword Pioneer
πΊ
Lone Wolf
(3)
π
Keyword Trendsetter Combo
(7)
π±
Topic Pioneer
π
Keyword Champion
(2)
π¬
Deep Specialist
(10)
π
Century Club
(28)
π
Trend Setter
ποΈ
Keyword Collector
(75)
π
Conference Pioneer
π₯
Unstoppable
(10)
Conferences
JMLR (14)
NIPS (8)
AISTATS (2)
COLT (2)
ICLR (1)
ICML (1)
Top co-authors
Research topics
Keywords
support vector machine
(13)
kernel methods
(9)
learning rate
(7)
oracle inequality
(6)
gaussian kernel
(3)
reproducing kernel hilbert space
(3)
statistical learning theory
(3)
density-based clustering
(2)
optimization algorithm
(2)
universal kernel
(2)
epsilon-insensitive loss
(2)
clustering algorithm
(2)
cluster tree
(2)
hinge loss
(2)
kernel density estimation
(2)
risk minimization
(2)
unsupervised learning
(2)
hierarchical clustering
(2)
neural tangent kernel
(2)
quantile regression
(2)
Papers
Better by default: Strong pre-tuned MLPs and boosted trees on tabular data
NIPS 2024
A Framework and Benchmark for Deep Batch Active Learning for Regression
JMLR 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
NIPS 2023
Adaptive Clustering Using Kernel Density Estimators
JMLR 2023
Utilizing Expert Features for Contrastive Learning of Time-Series Representations
ICML 2022
Improved Classification Rates for Localized SVMs
JMLR 2022
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
JMLR 2022
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning
ICLR 2022
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms
JMLR 2020
Kernel Density Estimation for Dynamical Systems
JMLR 2018
Spatial Decompositions for Large Scale SVMs
AISTATS 2017
Optimal Learning Rates for Localized SVMs
JMLR 2016
Towards an Axiomatic Approach to Hierarchical Clustering of Measures
JMLR 2015
Elicitation and Identification of Properties
COLT 2014
Consistency and Rates for Clustering with DBSCAN
AISTATS 2012
Optimal learning rates for least squares SVMs using Gaussian kernels
NIPS 2011
Adaptive Density Level Set Clustering
COLT 2011
Training SVMs Without Offset
JMLR 2011
Universal Kernels on Non-Standard Input Spaces
NIPS 2010
Fast Learning from Non-i.i.d. Observations
NIPS 2009
Sparsity of SVMs that use the epsilon-insensitive loss
NIPS 2008
How SVMs can estimate quantiles and the median
NIPS 2007
An Oracle Inequality for Clipped Regularized Risk Minimizers
NIPS 2006
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
JMLR 2006
A Classification Framework for Anomaly Detection
JMLR 2005
On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition
JMLR 2004
Sparseness of Support Vector Machines
JMLR 2003
On the Influence of the Kernel on the Consistency of Support Vector Machines
JMLR 2001