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02/22/2023
Feature Partition Aggregation: A Fast Certified Defense Against a Union of Sparse Adversarial Attacks
Deep networks are susceptible to numerous types of adversarial attacks. ...
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12/09/2022
Training Data Influence Analysis and Estimation: A Survey
Good models require good training data. For overparameterized deep model...
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10/21/2022
TCAB: A Large-Scale Text Classification Attack Benchmark
We introduce the Text Classification Attack Benchmark (TCAB), a dataset ...
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08/29/2022
Reducing Certified Regression to Certified Classification
Adversarial training instances can severely distort a model's behavior. ...
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05/23/2022
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees
We propose Instance-Based Uncertainty estimation for Gradient-boosted re...
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04/30/2022
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees
Influence estimation analyzes how changes to the training data can lead ...
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01/25/2022
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation
Targeted training-set attacks inject malicious instances into the traini...
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01/21/2022
Identifying Adversarial Attacks on Text Classifiers
The landscape of adversarial attacks against text classifiers continues ...
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09/11/2020
DART: Data Addition and Removal Trees
How can we update data for a machine learning model after it has already...
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09/11/2020
TREX: Tree-Ensemble Representer-Point Explanations
How can we identify the training examples that contribute most to the pr...
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02/24/2020
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift
Positive-unlabeled (PU) learning trains a binary classifier using only p...
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01/14/2020
EGGS: A Flexible Approach to Relational Modeling of Social Network Spam
Social networking websites face a constant barrage of spam, unwanted mes...
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06/23/2018
On Adversarial Examples for Character-Level Neural Machine Translation
Evaluating on adversarial examples has become a standard procedure to me...
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12/19/2017
HotFlip: White-Box Adversarial Examples for NLP
Adversarial examples expose vulnerabilities of machine learning models. ...
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11/10/2017
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation
The study and understanding of human behaviour is relevant to computer s...
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04/01/2015
The Libra Toolkit for Probabilistic Models
The Libra Toolkit is a collection of algorithms for learning and inferen...
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10/16/2012
Closed-Form Learning of Markov Networks from Dependency Networks
Markov networks (MNs) are a powerful way to compactly represent a joint ...
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06/13/2012