## Publications

### 2012

- On the Hardness of Domain Adaptataion (And the Utility of Unlabeled Target Samples)

Shai Ben-David and Ruth Urner ALT 2012 - Weighted Clustering

Margareta Ackerman, Shai Ben-David, Simina Branzei, David Loker AAAI 2012 - Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss

Shai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan ICML 2012 - Domain Adaptation--Can Quantity compensate for Quality?

Shai Ben-David, Shai Shalev-Shwartz, and Ruth Urner ISAIM 2012 - Learning from Weak Teachers

Shai Ben-David, Ruth Urner and Ohad Shamir AISTATS 2012

### 2011

- Learning a Classifier when the Labeling Is Known

Shalev Ben-David, Shai Ben-David ALT 2011 - Multiclass Learnability and the ERM principle

Amit Daniely, Sivan Sabato, Shai Ben-David and Shai Shalev-Shwartz

Winner of Best Student Paper Award - Access to Unlabeled Data can Speed up Prediction Time

Ruth Urner, Shai Shalev-Shwartz, Shai Ben-David ICML 2011 - Discerning Linkage-Based Algorithms among Hierarchical Clustering Methods

Margareta Ackerman, Shai Ben-David IJCAI 2011

### 2010

- Characterization of linkage based clustering

Margareta Ackerman, Shai Ben-David, David Loker COLT 2010 - Impossibility Theorems for Domain Adaptation

Shai Ben David, Tyler Lu, Teresa Luu, David Pal AISTATS 2010 - Towards Property-Based Classification of Clustering Paradigms

Margareta Ackerman, Shai Ben-David, David Loker NIPS 2010 - A theory of learning from different domains

Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan: Machine Learning 79(1-2): 151-175 (2010) - A probabilistic duplicate detection system

George Beskales, Mohamed A. Soliman, Ihab F. Ilyas, Shai Ben-David, Yubin Kim ICDE 2010

### 2009

- Learning Low-Density Separators

Shai Ben-David, Tyler Lu, David Pal, and Miroslava Stakova AISTATS 2009 - Which Data Sets are Clusterable? - A Theoretical Study of Clusterability

Margarita Ackerman and S. Ben-David AISTATS 2009 - A Uniqueness Theorem for Clustering

Reza Bosagh Zadeh, Shai Ben-David UAI 2009 - Agnostic Online Learning

Shai Ben-David, David Pal and Shai Shalev-Shwartz COLT09 - Modeling and Querying Possible Repairs in Duplicate Detection

George Beskales, Mohamed A. Soliman, Ihab F. Ilyas and Shai Ben-David VLDB 2009

### 2008

- Does Unlabeled Data Provably Help?
Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning

Shai Ben-David, Tyler Lu and David Pal COLT 2008 - Relating Clustering Stability to Properties of Cluster Boundaries

Shai Ben-David, Ulrike von Luxburg COLT 2008 - Measures of Clustering Quality: A Working Set of Axioms for Clustering

Margarita Ackerman and S. Ben-David NIPS 2008 - A notion of task relatedness yielding provable multiple-task learning guarantees

Shai Ben-David, Reba Schuller Borbely. Machine Learning 73(3): 273-287 (2008) - Data Representation Framework Addressing the Training/Test Distributions Gap

Shai Ben-David. Book chapter in Dataset Shift in machine learning J.,Q., Candela, N. Lawrence, A., Schwaighofer and M., Sugiyama (Eds), MIT press, 2008.

### 2007

- Stability of k -Means Clustering

Shai Ben-David, David Pal, Hans-Ulrich Simon. COLT 2008 - A framework for statistical clustering with constant time approximation algorithms for K-median and K-means clustering

Shai Ben-David. Machine Learning 66(2-3): 243-257 (2007)

### 2006

- Learning Bounds for Support Vector Machines with Learned Kernels

Nathan Srebro, Shai Ben-David COLT'06 -
A Sober Look at Stability of Clustering

S. Ben-David, U. von Luxburg, D. Pal**Winner of Best Student Paper Award**in COLT'06 -
Alternative Measures of Computational Complexity

S. Ben-David TAMC'06 -
Towards a Statistical Theory of Clustering

(with Ulrike von Luxburg) - PASCAL Workshop on Statistics and Optimization of Clustering (2005) -
Non-Parametric Change Detection in 2D Random Sensor Fields

(with Ting He and Lang Tong)**Winner of Best Student Paper Award**in ICASSP 2005 -
A Framework for Statistical Clustering with Constant Time Approximation for K-Means Clustering

Journal of Machine Learning, 2006. - Analysis of Representations for Domain Adaptation

Shai Ben-David, John Blitzer, Koby Crammer and Fernando Pereira NIPS 2006

### Earlier publications.

A list of other publications can be found here.