Search Results for author: Shaul Markovitch

Found 13 papers, 3 papers with code

Knowledge-Based Learning through Feature Generation

no code implementations6 Jun 2020 Michal Badian, Shaul Markovitch

We assume that, in addition to the training set, we have access to additional datasets.

Text Classification Transfer Learning

A Two-Stage Masked LM Method for Term Set Expansion

1 code implementation ACL 2020 Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg

We tackle the task of Term Set Expansion (TSE): given a small seed set of example terms from a semantic class, finding more members of that class.

Textual Membership Queries

2 code implementations11 May 2018 Jonathan Zarecki, Shaul Markovitch

It uses a small amount of labeled data as the core set for the synthesis of useful membership queries (MQs) - unlabeled instances generated by an algorithm for human labeling.

Active Learning General Classification +1

Recursive Feature Generation for Knowledge-based Learning

no code implementations31 Jan 2018 Lior Friedman, Shaul Markovitch

With the increasing availability of well-formed collaborative knowledge bases, the performance of learning algorithms could be significantly enhanced if a way were found to exploit these knowledge bases.

General Classification Text Classification

Approximating Hierarchical MV-sets for Hierarchical Clustering

no code implementations NeurIPS 2014 Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch

The goal of hierarchical clustering is to construct a cluster tree, which can be viewed as the modal structure of a density.

Density Estimation

Learning to Predict from Textual Data

no code implementations4 Feb 2014 Kira Radinsky, Sagie Davidovich, Shaul Markovitch

Our Pundit algorithm generalizes examples of causality pairs to infer a causality predictor.

Language Modelling

Online Speedup Learning for Optimal Planning

no code implementations23 Jan 2014 Carmel Domshlak, Erez Karpas, Shaul Markovitch

A description of a planning task consists of an initial world state, a goal, and a set of actions for modifying the world state.

online learning

Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach

no code implementations15 Jan 2014 Saher Esmeir, Shaul Markovitch

ACT is an anytime algorithm that allows learning time to be increased in return for lower classification costs.

General Classification

Wikipedia-based Semantic Interpretation for Natural Language Processing

no code implementations15 Jan 2014 Evgeniy Gabrilovich, Shaul Markovitch

We evaluate the effectiveness of our method on text categorization and on computing the degree of semantic relatedness between fragments of natural language text.

Common Sense Reasoning Natural Language Processing +1

q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions

no code implementations NeurIPS 2013 Assaf Glazer, Michael Lindenbaum, Shaul Markovitch

In this paper we introduce a novel method that can efficiently estimate a family of hierarchical dense sets in high-dimensional distributions.

Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data

no code implementations NeurIPS 2012 Assaf Glazer, Michael Lindenbaum, Shaul Markovitch

We propose an efficient, generalized, nonparametric, statistical Kolmogorov-Smirnov test for detecting distributional change in high-dimensional data.

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