← Authors

Boaz Nadler

20 papers · 2006–2024 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (18) 🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (13) 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (106) πŸ“ˆ Trend Setter πŸ’Ž Century Club (20) πŸš€ Conference Pioneer

Conferences

NIPS (6) ICML (5) AISTATS (4) JMLR (2) CVPR (1) ICCV (1) ICLR (1)

Top co-authors

Yuval Kluger (6) Ariel Jaffe (4) Roi Weiss (3) Meirav Galun (2) Fred A. Hamprecht (2) Pini Zilber (2) Yaniv Tenzer (2) Uri Shaham (2) Ronen Basri (2) Omer Dror (2)

Keywords

spectral method (4) unsupervised learning (3) semi-supervised learning (2) spectral clustering (2) parameter estimation (2) support vector machine (2) kernel methods (2) sparse classification (2) hidden markov model (2) unlabeled datum (2) mixed linear regression (1) clustering analysis (1) graph clustering (1) feature selection (1) orthogonal matching pursuit (1) manifold regularization (1) image reconstruction (1) image segmentation (1) communication complexity (1) laplacian regularization (1)

Papers

Recovery Guarantees for Distributed-OMP AISTATS 2024
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data NIPS 2024
Truth is Universal: Robust Detection of Lies in LLMs NIPS 2024
Imbalanced Mixed Linear Regression NIPS 2023
Crowdsourcing Regression: A Spectral Approach AISTATS 2022
Inductive Matrix Completion: No Bad Local Minima and a Fast Algorithm ICML 2022
Beyond Trees: Classification with Sparse Pairwise Dependencies JMLR 2020
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach ICML 2018
SpectralNet: Spectral Clustering using Deep Neural Networks ICLR 2018
Cost efficient gradient boosting NIPS 2017
Fast Detection of Curved Edges at Low SNR CVPR 2016
Unsupervised Ensemble Learning with Dependent Classifiers AISTATS 2016
A Deep Learning Approach to Unsupervised Ensemble Learning ICML 2016
Learning Parametric-Output HMMs with Two Aliased States ICML 2015
Estimating the accuracies of multiple classifiers without labeled data AISTATS 2015
Accurate Blur Models vs. Image Priors in Single Image Super-resolution ICCV 2013
On learning parametric-output HMMs ICML 2013
Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data NIPS 2009
Universal Kernel-Based Learning with Applications to Regular Languages JMLR 2009
Fundamental Limitations of Spectral Clustering NIPS 2006