Ran Gilad-Bachrach

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 40

Top Topics

Regression Trees

Feature Importance

High Throughput

Top Venues

IACR Cryptol. ePrint Arch.

Publications

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach
The Intelligible and Effective Graph Neural Additive Networks. CoRR (2024)
Nir Weingarten, Zohar Yakhini, Moshe Butman, Ran Gilad-Bachrach
Tighter Bounds on the Information Bottleneck with Application to Deep Learning. CoRR (2024)
Chaya Ben Yehuda, Ran Gilad-Bachrach, Yarin Udi
Improving Engagement and Efficacy of mHealth Micro-Interventions for Stress Coping: an In-The-Wild Study. CoRR (2024)
Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach
TREE-G: Decision Trees Contesting Graph Neural Networks. AAAI (2024)
Hofit Wasserman Rozen, Niva Elkin-Koren, Ran Gilad-Bachrach
The Case Against Explainability. CoRR (2023)
Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson
Graph Neural Networks Use Graphs When They Shouldn't. CoRR (2023)
Yonatan E. Brand, Dafna Schwartz, Eran Gazit, Aron S. Buchman, Ran Gilad-Bachrach, 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 22 (18) (2022)
Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach
A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits. AISTATS (2022)
Nimrod Harel, Ran Gilad-Bachrach, Uri Obolski
Inherent Inconsistencies of Feature Importance. CoRR (2022)
Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach
Graph Trees with Attention. CoRR (2022)
Omri Armstrong, Ran Gilad-Bachrach
Robust Model Compression Using Deep Hypotheses. CoRR (2021)
Brit Youngmann, Elad Yom-Tov, Ran Gilad-Bachrach, Danny Karmon
Algorithmic copywriting: automated generation of health-related advertisements to improve their performance. Inf. Retr. J. 24 (3) (2021)
Omri Armstrong, Ran Gilad-Bachrach
Robust Model Compression Using Deep Hypotheses. AAAI (2021)
Pierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach
Break your Bandit Routine with LSD Rewards: a Last Switch Dependent Analysis of Satiation and Seasonality. CoRR (2021)
Christopher Pyles, François van Schalkwyk, Gerard J. Gorman, Marijan Beg, Lee Stott, Nir Levy, Ran Gilad-Bachrach
PyBryt: auto-assessment and auto-grading for computational thinking. CoRR (2021)
Amnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Weiss-Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach
Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data. ICML (2021)
Roy Hirsch, Ran Gilad-Bachrach
Trees with Attention for Set Prediction Tasks. ICML (2021)
Brit Youngmann, Elad Yom-Tov, Ran Gilad-Bachrach, Danny Karmon
The Automated Copywriter: Algorithmic Rephrasing of Health-Related Advertisements to Improve their Performance. WWW (2020)
Amnon Catav, Boyang Fu, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach
Marginal Contribution Feature Importance - an Axiomatic Approach for The Natural Case. CoRR (2020)
Oded Vainas, Ori Bar-Ilan, Yossi Ben David, Ran Gilad-Bachrach, Galit Lukin, Meitar Ronen, Roi Shillo, Daniel Sitton
E-Gotsky: Sequencing Content using the Zone of Proximal Development. CoRR (2019)
Brit Youngmann, Ran Gilad-Bachrach, Danny Karmon, Elad Yom-Tov
The Automated Copywriter: Algorithmic Rephrasing of Health-Related Advertisements to Improve their Performance. CoRR (2019)
Alon Brutzkus, Ran Gilad-Bachrach, Oren Elisha
Low Latency Privacy Preserving Inference. ICML (2019)
Ran Gilad-Bachrach, Kim Laine, Kristin E. Lauter, Peter Rindal, Mike Rosulek
Secure Data Exchange: A Marketplace in the Cloud. CCSW@CCS (2019)
Oded Vainas, Yossi Ben David, Ran Gilad-Bachrach, Meitar Ronen, Ori Bar-Ilan, Roi Shillo, Galit Lukin, Daniel Sitton
Staying in the Zone: Sequencing Content in Classrooms Based on the Zone of Proximal Development. EDM (2019)
Stav Buchsbaum, Ran Gilad-Bachrach, Yehuda Lindell
Turning Lemons into Peaches using Secure Computation. CoRR (2018)
John Moore, Joel Pfeiffer, Kai Wei, Rishabh K. Iyer, Denis Charles, Ran Gilad-Bachrach, Levi Boyles, Eren Manavoglu
Modeling and Simultaneously Removing Bias via Adversarial Neural Networks. CoRR (2018)
Alon Gonem, Ran Gilad-Bachrach
Smooth Sensitivity Based Approach for Differentially Private PCA. ALT (2018)
Hao Chen, Ran Gilad-Bachrach, Kyoohyung Han, Zhicong Huang, Amir Jalali, Kim Laine, Kristin E. Lauter
Logistic regression over encrypted data from fully homomorphic encryption. IACR Cryptol. ePrint Arch. 2018 (2018)
Alon Brutzkus, Oren Elisha, Ran Gilad-Bachrach
Low Latency Privacy Preserving Inference. CoRR (2018)
Nathan Dowlin, Ran Gilad-Bachrach, Kim Laine, Kristin E. Lauter, Michael Naehrig, John Wernsing
Manual for Using Homomorphic Encryption for Bioinformatics. Proc. IEEE 105 (3) (2017)
Alon Gonen, Ran Gilad-Bachrach
Smooth Sensitivity Based Approach for Differentially Private Principal Component Analysis. CoRR (2017)
Melissa Chase, Ran Gilad-Bachrach, Kim Laine, Kristin E. Lauter, Peter Rindal
Private Collaborative Neural Network Learning. IACR Cryptol. ePrint Arch. 2017 (2017)
Tauhidur Rahman, Mary Czerwinski, Ran Gilad-Bachrach, Paul Johns
Predicting "About-to-Eat" Moments for Just-in-Time Eating Intervention. Digital Health (2016)
Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin E. Lauter, Michael Naehrig, John Wernsing
CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy. ICML (2016)
Ran Gilad-Bachrach, Kim Laine, Kristin E. Lauter, Peter Rindal, Mike Rosulek
Secure Data Exchange: A Marketplace in the Cloud. IACR Cryptol. ePrint Arch. 2016 (2016)
Mary Czerwinski, Ran Gilad-Bachrach, Shamsi T. Iqbal, Gloria Mark
Challenges for designing notifications for affective computing systems. UbiComp Adjunct (2016)
Petr Slovák, Christopher Frauenberger, Ran Gilad-Bachrach, Mia Doces, Brian Smith, Rachel Kamb, Kael Rowan, Geraldine Fitzpatrick
Scaffolding the scaffolding: Supporting children¿s social-emotional learning at home. CSCW (2016)
Korlakai Vinayak Rashmi, Ran Gilad-Bachrach
DART: Dropouts meet Multiple Additive Regression Trees. AISTATS (2015)
Petr Slovák, Ran Gilad-Bachrach, Geraldine Fitzpatrick
Designing Social and Emotional Skills Training: The Challenges and Opportunities for Technology Support. CHI (2015)
K. V. Rashmi, Ran Gilad-Bachrach
DART: Dropouts meet Multiple Additive Regression Trees. CoRR (2015)
Pengtao Xie, Misha Bilenko, Tom Finley, Ran Gilad-Bachrach, Kristin E. Lauter, Michael Naehrig
Crypto-Nets: Neural Networks over Encrypted Data. CoRR (2014)
Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach, Liran Katzir, Noam Koenigstein, Nir Nice, Ulrich Paquet
Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces. RecSys (2014)
Pablo Paredes, Ran Gilad-Bachrach, Mary Czerwinski, Asta Roseway, Kael Rowan, Javier Hernandez
PopTherapy: coping with stress through pop-culture. PervasiveHealth (2014)
Ran Gilad-Bachrach, Christopher J. C. Burges
Classifier selection using the predicate depth. J. Mach. Learn. Res. 14 (1) (2013)
Ran Gilad-Bachrach, Christopher J. C. Burges
The Median Hypothesis. Empirical Inference (2013)
Jason D. Lee, Ran Gilad-Bachrach, Rich Caruana
Using Multiple Samples to Learn Mixture Models. CoRR (2013)
Jason D. Lee, Ran Gilad-Bachrach, Rich Caruana
Using multiple samples to learn mixture models. NIPS (2013)
Karthik Raman, Krysta M. Svore, Ran Gilad-Bachrach, Christopher J. C. Burges
Learning from mistakes: towards a correctable learning algorithm. CIKM (2012)
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao
Optimal Distributed Online Prediction Using Mini-Batches. J. Mach. Learn. Res. 13 (2012)
Trang Thai, Gerald DeJean, Ran Gilad-Bachrach
Confined intra-arm communication for medical applications. Wireless Health (2012)
Moshe Gabel, Assaf Schuster, Ran Gilad-Bachrach, Nikolaj Bjørner
Latent fault detection in large scale services. DSN (2012)
Moshe Gabel, Ran Gilad-Bachrach, Erin Renshaw, Assaf Schuster
Full body gait analysis with Kinect. EMBC (2012)
Ashok Kumar Ponnuswami, Kumaresh Pattabiraman, Qiang Wu, Ran Gilad-Bachrach, Tapas Kanungo
On composition of a federated web search result page: using online users to provide pairwise preference for heterogeneous verticals. WSDM (2011)
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao
Optimal Distributed Online Prediction. ICML (2011)
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao
Optimal Distributed Online Prediction using Mini-Batches CoRR (2010)
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin Xiao
Robust Distributed Online Prediction CoRR (2010)
Ran Gilad-Bachrach, Aharon Bar-Hillel, Liat Ein-Dor
Efficient human computation: the distributed labeling problem. KDD Workshop on Human Computation (2009)
Ran Gilad-Bachrach, Aharon Bar-Hillel, Liat Ein-Dor
Efficient Human Computation CoRR (2009)
Aharon Bar-Hillel, Amir Di-Nur, Liat Ein-Dor, Ran Gilad-Bachrach, Yossi Ittach
Workstation capacity tuning using reinforcement learning. SC (2007)
Amir Navot, Ran Gilad-Bachrach, Yiftah Navot, Naftali Tishby
Is Feature Selection Still Necessary? SLSFS (2005)
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
Query by Committee Made Real. NIPS (2005)
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
Bayes and Tukey Meet at the Center Point. COLT (2004)
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
Margin based feature selection - theory and algorithms. ICML (2004)
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
An Information Theoretic Tradeoff between Complexity and Accuracy. COLT (2003)
Koby Crammer, Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
Margin Analysis of the LVQ Algorithm. NIPS (2002)
Shai Fine, Ran Gilad-Bachrach, Eli Shamir
Query by committee, linear separation and random walks. Theor. Comput. Sci. 284 (1) (2002)