Ran Gilad-Bachrach

Orcid: 0000-0002-4001-8307

Affiliations:
  • Microsoft Research Redmond, WA, USA


According to our database1, Ran Gilad-Bachrach authored at least 62 papers between 1997 and 2024.

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Bibliography

2024
Tighter Bounds on the Information Bottleneck with Application to Deep Learning.
CoRR, 2024

TREE-G: Decision Trees Contesting Graph Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Graph Neural Networks Use Graphs When They Shouldn't.
CoRR, 2023

The Case Against Explainability.
CoRR, 2023

2022
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, 2022

Graph Trees with Attention.
CoRR, 2022

Inherent Inconsistencies of Feature Importance.
CoRR, 2022

A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Algorithmic copywriting: automated generation of health-related advertisements to improve their performance.
Inf. Retr. J., 2021

PyBryt: auto-assessment and auto-grading for computational thinking.
CoRR, 2021

Break your Bandit Routine with LSD Rewards: a Last Switch Dependent Analysis of Satiation and Seasonality.
CoRR, 2021

Trees with Attention for Set Prediction Tasks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data.
Proceedings of the 38th International Conference on Machine Learning, 2021

Robust Model Compression Using Deep Hypotheses.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Marginal Contribution Feature Importance - an Axiomatic Approach for The Natural Case.
CoRR, 2020

The Automated Copywriter: Algorithmic Rephrasing of Health-Related Advertisements to Improve their Performance.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

2019
E-Gotsky: Sequencing Content using the Zone of Proximal Development.
CoRR, 2019

Low Latency Privacy Preserving Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

Staying in the Zone: Sequencing Content in Classrooms Based on the Zone of Proximal Development.
Proceedings of the 12th International Conference on Educational Data Mining, 2019

2018
Logistic regression over encrypted data from fully homomorphic encryption.
IACR Cryptol. ePrint Arch., 2018

Turning Lemons into Peaches using Secure Computation.
CoRR, 2018

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks.
CoRR, 2018

Smooth Sensitivity Based Approach for Differentially Private PCA.
Proceedings of the Algorithmic Learning Theory, 2018

2017
Manual for Using Homomorphic Encryption for Bioinformatics.
Proc. IEEE, 2017

Private Collaborative Neural Network Learning.
IACR Cryptol. ePrint Arch., 2017

Smooth Sensitivity Based Approach for Differentially Private Principal Component Analysis.
CoRR, 2017

2016
Secure Data Exchange: A Marketplace in the Cloud.
IACR Cryptol. ePrint Arch., 2016

CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Challenges for designing notifications for affective computing systems.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2016 ACM International Symposium on Wearable Computers, 2016

Predicting "About-to-Eat" Moments for Just-in-Time Eating Intervention.
Proceedings of the 6th International Conference on Digital Health Conference, 2016

Scaffolding the scaffolding: Supporting children¿s social-emotional learning at home.
Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 2016

2015
Designing Social and Emotional Skills Training: The Challenges and Opportunities for Technology Support.
Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 2015

DART: Dropouts meet Multiple Additive Regression Trees.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Crypto-Nets: Neural Networks over Encrypted Data.
CoRR, 2014

Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces.
Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

PopTherapy: coping with stress through pop-culture.
Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare, 2014

2013
Classifier selection using the predicate depth.
J. Mach. Learn. Res., 2013

Using multiple samples to learn mixture models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

The Median Hypothesis.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
Optimal Distributed Online Prediction Using Mini-Batches.
J. Mach. Learn. Res., 2012

Confined intra-arm communication for medical applications.
Proceedings of the Wireless Health 2012, 2012

Full body gait analysis with Kinect.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Latent fault detection in large scale services.
Proceedings of the IEEE/IFIP International Conference on Dependable Systems and Networks, 2012

Learning from mistakes: towards a correctable learning algorithm.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
On composition of a federated web search result page: using online users to provide pairwise preference for heterogeneous verticals.
Proceedings of the Forth International Conference on Web Search and Web Data Mining, 2011

Optimal Distributed Online Prediction.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Robust Distributed Online Prediction
CoRR, 2010

2009
Efficient Human Computation
CoRR, 2009

Efficient human computation: the distributed labeling problem.
Proceedings of the ACM SIGKDD Workshop on Human Computation, Paris, France, June 28, 2009, 2009

2007
Workstation capacity tuning using reinforcement learning.
Proceedings of the ACM/IEEE Conference on High Performance Networking and Computing, 2007

2006
To PAC and beyond (למידה מונחית ומעבר לה.; Probably approximately correct learning.).
PhD thesis, 2006

Large Margin Principles for Feature Selection.
Proceedings of the Feature Extraction - Foundations and Applications, 2006

Margin Based Feature Selection and Infogain with Standard Classifiers.
Proceedings of the Feature Extraction - Foundations and Applications, 2006

2005
Is Feature Selection Still Necessary?
Proceedings of the Subspace, 2005

Query by Committee Made Real.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004
Margin based feature selection - theory and algorithms.
Proceedings of the Machine Learning, 2004

Bayes and Tukey Meet at the Center Point.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
An Information Theoretic Tradeoff between Complexity and Accuracy.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Query by committee, linear separation and random walks.
Theor. Comput. Sci., 2002

On the Competitive Theory and Practice of Online List Accessing Algorithms.
Algorithmica, 2002

Margin Analysis of the LVQ Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

1997
Online List Accessing Algorithms and Their Applications: Recent Empirical Evidence.
Proceedings of the Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 1997


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