1 code implementation • ICML 2018 • Ariel Jaffe, Roi Weiss, Shai Carmi, Yuval Kluger, Boaz Nadler
Latent variable models with hidden binary units appear in various applications.
no code implementations • NeurIPS 2017 • Aryeh Kontorovich, Sivan Sabato, Roi Weiss
We examine the Bayes-consistency of a recently proposed 1-nearest-neighbor-based multiclass learning algorithm.
no code implementations • 1 Jul 2014 • Aryeh Kontorovich, Roi Weiss
We show that a simple modification of the 1-nearest neighbor classifier yields a strongly Bayes consistent learner.
no code implementations • 7 Feb 2015 • Roi Weiss, Boaz Nadler
In various applications involving hidden Markov models (HMMs), some of the hidden states are aliased, having identical output distributions.
no code implementations • 30 Jan 2014 • Aryeh Kontorovich, Roi Weiss
We prove generalization bounds that match the state of the art in sample size $n$ and significantly improve the dependence on the number of classes $k$.
no code implementations • 24 Jun 2019 • Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss
This is the first learning algorithm known to enjoy this property; by comparison, the $k$-NN classifier and its variants are not generally universally Bayes-consistent, except under additional structural assumptions, such as an inner product, a norm, finite dimension, or a Besicovitch-type property.
no code implementations • 1 Oct 2020 • László Györfi, Roi Weiss
We first obtain rates for the standard $k$-NN rule under a margin condition and a new generalized-Lipschitz condition.
no code implementations • 23 Nov 2021 • László Györfi, Aryeh Kontorovich, Roi Weiss
data we identify an optimal tree $T^*$ and efficiently construct a tree density estimate $f_n$ such that, without any regularity conditions on the density $f$, one has $\lim_{n\to \infty} \int |f_n(\boldsymbol x)-f_{T^*}(\boldsymbol x)|d\boldsymbol x=0$ a. s. For Lipschitz $f$ with bounded support, $\mathbb E \left\{ \int |f_n(\boldsymbol x)-f_{T^*}(\boldsymbol x)|d\boldsymbol x\right\}=O\big(n^{-1/4}\big)$, a dimension-free rate.
no code implementations • 16 Jun 2022 • Omer Kerem, Roi Weiss
We first show that OptiNet achieves non-trivial compression rates while enjoying near minimax-optimal error rates.
no code implementations • 24 Oct 2023 • Lee-Ad Gottlieb, Timor Sharabi, Roi Weiss
The problem of nearest neighbor condensing has enjoyed a long history of study, both in its theoretical and practical aspects.
no code implementations • 16 Feb 2024 • Elad Aigner-Horev, Daniel Rozenberg, Roi Weiss
We study the statistical resilience of high-dimensional data.