Ariel Jaffe

According to our database, Ariel Jaffe authored at least 17 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Spectral Self-supervised Feature Selection.

Daniel Segal, Ofir Lindenbaum, Ariel Jaffe

CoRR, 2024

2023

Multi-modal differentiable unsupervised feature selection.

Junchen Yang, Ofir Lindenbaum, Yuval Kluger, Ariel Jaffe

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

DiSC: Differential Spectral Clustering of Features.

Ram Dyuthi Sristi, Gal Mishne, Ariel Jaffe

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Spectral Neighbor Joining for Reconstruction of Latent Tree Models.

Ariel Jaffe, Noah Amsel, Yariv Aizenbud, Boaz Nadler, Joseph T. Chang, Yuval Kluger

SIAM J. Math. Data Sci., 2021

Spectral Top-Down Recovery of Latent Tree Models.

Yariv Aizenbud, Ariel Jaffe, Meng Wang, Amber Hu, Noah Amsel, Boaz Nadler, Joseph T. Chang, Yuval Kluger

CoRR, 2021

2020

Randomized near-neighbor graphs, giant components and applications in data science.

Ariel Jaffe, Yuval Kluger, George C. Linderman, Gal Mishne, Stefan Steinerberger

J. Appl. Probab., 2020

The Spectral Underpinning of word2vec.

Ariel Jaffe, Yuval Kluger, Ofir Lindenbaum, Jonathan Patsenker, Erez Peterfreund, Stefan Steinerberger

Frontiers Appl. Math. Stat., 2020

Super-resolution multi-reference alignment.

Tamir Bendory, Ariel Jaffe, William E. Leeb, Nir Sharon, Amit Singer

CoRR, 2020

Spectral neighbor joining for reconstruction of latent tree models.

Ariel Jaffe, Noah Amsel, Boaz Nadler, Joseph T. Chang, Yuval Kluger

CoRR, 2020

2018

Newton Correction Methods for Computing Real Eigenpairs of Symmetric Tensors.

Ariel Jaffe, Roi Weiss, Boaz Nadler

SIAM J. Matrix Anal. Appl., 2018

Learning Binary Latent Variable Models: A Tensor Eigenpair Approach.

Ariel Jaffe, Roi Weiss, Shai Carmi, Yuval Kluger, Boaz Nadler

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Minimax-optimal semi-supervised regression on unknown manifolds.

Amit Moscovich, Ariel Jaffe, Boaz Nadler

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

A Deep Learning Approach to Unsupervised Ensemble Learning.

Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger

Proceedings of the 33nd International Conference on Machine Learning, 2016

CUDA implementation of an optimal online Gaussian-Signal-in-Gaussian-Noise detector.

Nir Nossenson, Ariel J. Jaffe

Proceedings of the 2016 IEEE High Performance Extreme Computing Conference, 2016

Unsupervised Ensemble Learning with Dependent Classifiers.

Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Estimating the accuracies of multiple classifiers without labeled data.

Ariel Jaffe, Boaz Nadler, Yuval Kluger

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Single-Site Localization via Maximum Discrimination Multipath Fingerprinting.

Ariel Jaffe, Mati Wax

IEEE Trans. Signal Process., 2014