Yuval Kluger
20 papers · 2015–2025 · 6 venues · across top CS/AI venues
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Achievements
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Research topics
Machine Learning
(18)
Core Methods
(16)
Learning Types
(10)
Deep Learning
(9)
Artificial Intelligence
(6)
Architectures
(6)
Core AI
(6)
Optimization & Theory
(4)
Models
(3)
Computer Vision
(2)
Application Areas
(2)
Generation
(2)
Data Science & Analytics
(1)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Keywords
feature selection
(5)
unsupervised learning
(4)
graph laplacian
(4)
neural network
(3)
multimodal learning
(3)
spectral method
(3)
spectral clustering
(2)
high-dimensional data
(2)
riemannian geometry
(2)
unsupervised feature selection
(2)
deep neural network
(2)
embedding
(1)
sparse representation
(1)
visual question answering
(1)
link prediction
(1)
parameter estimation
(1)
wavelet transform
(1)
transductive learning
(1)
manifold learning
(1)
interpretable machine learning
(1)
Papers
Dual Diffusion for Unified Image Generation and Understanding
CVPR 2025
Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
ICML 2025
Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps
ICLR 2024
Transductive and Inductive Outlier Detection with Robust Autoencoders
UAI 2024
Few-Sample Feature Selection via Feature Manifold Learning
ICML 2023
GEASS: Neural causal feature selection for high-dimensional biological data
ICLR 2023
Multi-modal differentiable unsupervised feature selection
UAI 2023
Towards Understanding and Reducing Graph Structural Noise for GNNs
ICML 2023
Crowdsourcing Regression: A Spectral Approach
AISTATS 2022
L0-Sparse Canonical Correlation Analysis
ICLR 2022
Locally Sparse Neural Networks for Tabular Biomedical Data
ICML 2022
Neural Inverse Transform Sampler
ICML 2022
Differentiable Unsupervised Feature Selection based on a Gated Laplacian
NeurIPS 2021
Hyperbolic Procrustes Analysis Using Riemannian Geometry
NeurIPS 2021
Feature Selection using Stochastic Gates
ICML 2020
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
ICML 2018
SpectralNet: Spectral Clustering using Deep Neural Networks
ICLR 2018
A Deep Learning Approach to Unsupervised Ensemble Learning
ICML 2016
Unsupervised Ensemble Learning with Dependent Classifiers
AISTATS 2016
Estimating the accuracies of multiple classifiers without labeled data
AISTATS 2015