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Publications

2024

Yarin Udi, Ran Gilad-Bachrach, Hilla Cohen, Lena Sagi-Dain

Impact of body mass index and examination type on utilization of screening programs: A big data study

Preventive Medicine

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

The Intelligible and Effective Graph Neural Additive Networks

arXiv:2406.01317

Ziv Hersh, Yiska Loewenberg Weisband, Ariel Bogan, Adir Leibovich, Uri Obolski, Daniel Nevo, Ran Gilad-Bachrach

Impact of Long-COVID in children: a large cohort study

Child and Adolescent Psychiatry and Mental Health

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

TREE-G: Decision Trees Contesting Graph Neural Networks

Proceedings of the AAAI Conference on Artificial Intelligence

Nir Weingarten, Zohar Yakhini, Moshe Butman, Ran Gilad-Bachrach

Tighter Bounds on the Information Bottleneck with Application to Deep Learning

arXiv:2402.07639

2023

A Work in Progress: Tighter Bounds on the Information Bottleneck for Deep Learning

Nir Weingarten, Moshe Butman, Ran Gilad-Bachrach

NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems

דלית קן־דרור פלדמן, קרין נהון, ורדית אבידן ורן גלעד בכרך

זיוף, זיוף עמוק (Deep-Fake), חוק הסרטונים ועקרון הפרשנות המצמצמת: מה הדין?

המשפט

Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

Graph Neural Networks Use Graphs When They Shouldn't

arXiv:2309.04332

Hofit Wasserman-Rozen, Ran Gilad-Bachrach, Niva Elkin-Koren

Lost in Translation: The Limits of Explainability in AI

SSRN 4531323

Hofit Wasserman Rozen, Niva Elkin-Koren, and Ran Gilad-Bachrach

The Case Against Explainability

arXiv:2305.12167

2022

Yonatan E. Brand, Dafna Schwartz, Eran Gazit, Aron S. Buchman, Ran Gilad-Bachrach and Jeffrey M. Hausdorff

Gait Detection from a Wrist-Worn Sensor Using Machine Learning Methods: A Daily Living Study in Older Adults and People with Parkinson’s Disease

Sensors

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

Graph Trees with Attention

arXiv:2207.02760

Nimrod Harel, Ran Gilad-Bachrach, Uri Obolski

Inherent Inconsistencies of Feature Importance

arXiv:2206.08204

Pierre Laforgue, Giulia Clerici, Nicol`o Cesa-Bianchi, Ran Gilad-Bachrach

A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits

The 25th International Conference on
Artificial Intelligence and Statistics (AIStats)

2021

Christopher Pyles, Francois van Schalkwyk, Gerard J. Gorman, Marijan Beg, Lee Stott, Nir Levy and Ran Gilad-Bachrach

PyBryt: auto-assessment and auto-grading for computational thinking

arXiv:2112.02144, 2021

Roy Hirsch, Ran Gilad-Bachrach

Trees with Attention for Set Prediction Tasks

International Conference on Machine Learning, 4250-4261

Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Libi Weiss Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach

Marginal Contribution Feature Importance-an Axiomatic Approach for Explaining Data

International Conference on Machine Learning, 1324-1335

Brit Youngmann, Elad Yom-Tov, Ran Gilad-Bachrach, Danny Karmon

Algorithmic copywriting: automated generation of health-related advertisements to improve their performance

Information Retrieval Journal 24 (3), 205-239

Sigal Shaklai, Ran Gilad-Bachrach, Elad Yom-Tov, Naftali Stern

Detecting Impending Stroke From Cognitive Traits Evident in Internet Searches: Analysis of Archival Data

Journal of Medical Internet Research 23 (5), e27084

Sigal Shaklai, Ran Gilad-Bachrach, Elad Yom-Tov, Naftali Stern

The First Predictor of Impending Stroke: An Internet Search-Based Algorithm Blind to Established Cardiometabolic Risk, Outperforms Classical Risk Factor-Based Calculators

Journal of the Endocrine Society 5 (Supplement_1), A299-A300

Omri Armstrong, Ran Gilad-Bachrach

Robust Model Compression Using Deep Hypotheses

Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 35. No. 8.

2020

Amnon Catav, Boyang Fu, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach

Marginal Contribution Feature Importance -- an Axiomatic Approach for The Natural Case

arXiv:2010.07910, 2020

Brit Youngmann, Elad Yom-Tov, Ran Gilad-Bachrach, Danny Karmon

The Automated Copywriter: Algorithmic Rephrasing of Health-Related Advertisements to Improve their Performance

WWW'20

2019

Gilad-Bachrach, Ran; Laine, Kim; Lauter, Kristin E.; Rindal, Peter & Rosulek, Mike

Secure Data Exchange: A Marketplace in the Cloud

{ACM} {SIGSAC} Conference on Cloud Computing Security Workshop (CCSW@CCS), 2019

Brutzkus, Alon; Gilad-Bachrach, Ran & Elisha, Oren

Low Latency Privacy Preserving Inference

36th International Conference on Machine Learning (ICML), 2019

Vainas, Oded; Bar-Ilan, Ori; David, Yossi Ben; Gilad-Bachrach, Ran; Lukin, Galit; Ronen, Meitar; Shillo, Roi & Sitton, Daniel

E-Gotsky: Sequencing Content using the Zone of Proximal Development

arXiv:1904.12268 , 2019

Youngmann, Brit; Gilad-Bachrach, Ran; Karmon, Danny & Yom-Tov, Elad

The Automated Copywriter: Algorithmic Rephrasing of Health-Related Advertisements to Improve their Performance

arXiv:1910.12274, 2019

Vainas, Oded; David, Yossi Ben; Gilad-Bachrach, Ran; Ronen, Meitar; Bar-Ilan, Ori; Shillo, Roi; Lukin, Galit & Sitton, Daniel

Staying in the Zone: Sequencing Content in Classrooms Based on the Zone of Proximal Development

12th International Conference on Educational Data Mining (EDM), 2019

2018

Chen, Hao; Gilad-Bachrach, Ran; Han, Kyoohyung; Huang, Zhicong; Jalali, Amir; Laine, Kim & Lauter, Kristin E.

Logistic regression over encrypted data from fully homomorphic encryption

ePrint:462, 2018

Gonem, Alon & Gilad-Bachrach, Ran

Smooth Sensitivity Based Approach for Differentially Private PCA

Algorithmic Learning Theory (ALT), 2018

Brutzkus, Alon; Elisha, Oren & Gilad-Bachrach, Ran

Low Latency Privacy Preserving Inference

arXiv:1812.10659, 2018

Buchsbaum, Stav; Gilad-Bachrach, Ran & Lindell, Yehuda

Turning Lemons into Peaches using Secure Computation

arXiv:1810.02066, 2018

Moore, John; Pfeiffer, Joel; Wei, Kai; Iyer, Rishabh K.; Charles, Denis; Gilad-Bachrach, Ran; Boyles, Levi & Manavoglu, Eren

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks

arXiv:1804.06909, 2018

2017

Yarin Udi, Ran Gilad-Bachrach, Hilla Cohen, Lena Sagi-Dain

Impact of body mass index and examination type on utilization of screening programs: A big data study

Preventive Medicine

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

The Intelligible and Effective Graph Neural Additive Networks

arXiv:2406.01317

Ziv Hersh, Yiska Loewenberg Weisband, Ariel Bogan, Adir Leibovich, Uri Obolski, Daniel Nevo, Ran Gilad-Bachrach

Impact of Long-COVID in children: a large cohort study

Child and Adolescent Psychiatry and Mental Health

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

TREE-G: Decision Trees Contesting Graph Neural Networks

Proceedings of the AAAI Conference on Artificial Intelligence

2016

Gilad-Bachrach, Ran; Laine, Kim; Lauter, Kristin E.; Rindal, Peter & Rosulek, Mike

Secure Data Exchange: A Marketplace in the Cloud

ePrint:620, 2016

Gilad-Bachrach, Ran; Dowlin, Nathan; Laine, Kim; Lauter, Kristin E.; Naehrig, Michael & Wernsing, John

CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy

33nd International Conference on Machine Learning (ICML), 2016

Rahman, Tauhidur; Czerwinski, Mary; Gilad-Bachrach, Ran & Johns, Paul

Predicting About-to-Eat" Moments for Just-in-Time Eating Intervention"

6th International Conference on Digital Health Conference (DH), 2016

Slovák, Petr; Frauenberger, Christopher; Gilad-Bachrach, Ran; Doces, Mia; Smith, Brian; Kamb, Rachel; Rowan, Kael & Fitzpatrick, Geraldine

Scaffolding the scaffolding: Supporting children\textquestiondowns social-emotional learning at home

19th {ACM} Conference on Computer-Supported Cooperative Work & Social Computing (CSCW), 2016

Czerwinski, Mary; Gilad-Bachrach, Ran; Iqbal, Shamsi T. & Mark, Gloria

Challenges for designing notifications for affective computing systems

{ACM} International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2016

2015

Rashmi, K. V. & Gilad-Bachrach, Ran

DART: Dropouts meet Multiple Additive Regression Trees

arXiv:1505.01866, 2015

Rashmi, Korlakai Vinayak & Gilad-Bachrach, Ran

DART: Dropouts meet Multiple Additive Regression Trees

8th International Conference on Artificial Intelligence and Statistics (AISTATS), 2015

Slovák, Petr; Gilad-Bachrach, Ran & Fitzpatrick, Geraldine

Designing Social and Emotional Skills Training: The Challenges and Opportunities for Technology Support

33rd Annual {ACM} Conference on Human Factors in Computing Systems (CHI), 2015

2014

Bachrach, Yoram; Finkelstein, Yehuda; Gilad-Bachrach, Ran; Katzir, Liran; Koenigstein, Noam; Nice, Nir & Paquet, Ulrich

Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces

Eighth {ACM} Conference on Recommender Systems (RecSys), 2014

Xie, Pengtao; Bilenko, Misha; Finley, Tom; Gilad-Bachrach, Ran; Lauter, Kristin E. & Naehrig, Michael

Crypto-Nets: Neural Networks over Encrypted Data

arXiv:1412.6181, 2014

Paredes, Pablo; Gilad-Bachrach, Ran; Czerwinski, Mary; Roseway, Asta; Rowan, Kael & Hernandez, Javier

PopTherapy: coping with stress through pop-culture

International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2014

2013

Lee, Jason D.; Gilad-Bachrach, Ran & Caruana, Rich

Using multiple samples to learn mixture models

Advances in Neural Information Processing Systems 26 (NIPS), 2013

Lee, Jason D.; Gilad-Bachrach, Ran & Caruana, Rich

Using Multiple Samples to Learn Mixture Models

arXiv:1311.7184, 2013

Gilad-Bachrach, Ran & Burges, Christopher J. C.

The Median Hypothesis

Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

Gilad-Bachrach, Ran & Burges, Christopher J. C.

Classifier selection using the predicate depth

The Journal of Machine Learning Research (JMLR) 14.1, 2013

2012

Dekel, Ofer; Gilad-Bachrach, Ran; Shamir, Ohad & Xiao, Lin

Optimal Distributed Online Prediction Using Mini-Batches

The Journal of Machine Learning Research (JMLR) 13, 2012

Gabel, Moshe; Schuster, Assaf; Gilad-Bachrach, Ran & Bj{\o}rner, Nikolaj

Latent fault detection in large scale services

{IEEE/IFIP} International Conference on Dependable Systems and Networks (DSN) 2012

Raman, Karthik; Svore, Krysta M.; Gilad-Bachrach, Ran & Burges, Christopher J. C.

Learning from mistakes: towards a correctable learning algorithm

21st {ACM} International Conference on Information and Knowledge Management (CIKM), 2012

Gabel, Moshe; Gilad-Bachrach, Ran; Renshaw, Erin & Schuster, Assaf

Full body gait analysis with Kinect

Annual International Conference of the {IEEE} Engineering in Medicine and Biology Society (EMBC), 2012

Thai, Trang; DeJean, Gerald & Gilad-Bachrach, Ran

Confined intra-arm communication for medical applications

Wireless Health (WH), 2012

2011

Dekel, Ofer; Gilad-Bachrach, Ran; Shamir, Ohad & Xiao, Lin

Optimal Distributed Online Prediction

28th International Conference on Machine Learning (ICML), 2011

Ponnuswami, Ashok Kumar; Pattabiraman, Kumaresh; Wu, Qiang; Gilad-Bachrach, Ran & Kanungo, Tapas

On composition of a federated web search result page: using online users to provide pairwise preference for heterogeneous verticals

4th International Conference on Web Search and Web Data Mining (WSDM), 2011

1997-2010

Yarin Udi, Ran Gilad-Bachrach, Hilla Cohen, Lena Sagi-Dain

Impact of body mass index and examination type on utilization of screening programs: A big data study

Preventive Medicine

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

The Intelligible and Effective Graph Neural Additive Networks

arXiv:2406.01317

Ziv Hersh, Yiska Loewenberg Weisband, Ariel Bogan, Adir Leibovich, Uri Obolski, Daniel Nevo, Ran Gilad-Bachrach

Impact of Long-COVID in children: a large cohort study

Child and Adolescent Psychiatry and Mental Health

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

TREE-G: Decision Trees Contesting Graph Neural Networks

Proceedings of the AAAI Conference on Artificial Intelligence

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