1 code implementation • 27 Jan 2024 • Rui Zhang, Rui Xin, Margo Seltzer, Cynthia Rudin
Interpretability is crucial for doctors, hospitals, pharmaceutical companies and biotechnology corporations to analyze and make decisions for high stakes problems that involve human health.
1 code implementation • NeurIPS 2023 • Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer
Our evaluation on 10 hypergraph benchmark datasets shows that CAT-Walk attains outstanding performance on temporal hyperedge prediction benchmarks in both inductive and transductive settings.
1 code implementation • NeurIPS 2023 • Chudi Zhong, Zhi Chen, Jiachang Liu, Margo Seltzer, Cynthia Rudin
In real applications, interaction between machine learning models and domain experts is critical; however, the classical machine learning paradigm that usually produces only a single model does not facilitate such interaction.
1 code implementation • 28 Nov 2022 • Rui Zhang, Rui Xin, Margo Seltzer, Cynthia Rudin
Regression trees are one of the oldest forms of AI models, and their predictions can be made without a calculator, which makes them broadly useful, particularly for high-stakes applications.
1 code implementation • 15 Nov 2022 • Ali Behrouz, Margo Seltzer
The problem of identifying anomalies in dynamic networks is a fundamental task with a wide range of applications.
no code implementations • 13 Oct 2022 • Ali Behrouz, Mathias Lecuyer, Cynthia Rudin, Margo Seltzer
Specifically, they rely on the discreteness of the loss function, which means that real-valued weights cannot be directly used.
1 code implementation • 12 Oct 2022 • Jiachang Liu, Chudi Zhong, Boxuan Li, Margo Seltzer, Cynthia Rudin
Specifically, our approach produces a pool of almost-optimal sparse continuous solutions, each with a different support set, using a beam-search algorithm.
3 code implementations • 19 Sep 2022 • Zijie J. Wang, Chudi Zhong, Rui Xin, Takuya Takagi, Zhi Chen, Duen Horng Chau, Cynthia Rudin, Margo Seltzer
Given thousands of equally accurate machine learning (ML) models, how can users choose among them?
2 code implementations • 16 Sep 2022 • Rui Xin, Chudi Zhong, Zhi Chen, Takuya Takagi, Margo Seltzer, Cynthia Rudin
We show three applications of the Rashomon set: 1) it can be used to study variable importance for the set of almost-optimal trees (as opposed to a single tree), 2) the Rashomon set for accuracy enables enumeration of the Rashomon sets for balanced accuracy and F1-score, and 3) the Rashomon set for a full dataset can be used to produce Rashomon sets constructed with only subsets of the data set.
2 code implementations • 23 Feb 2022 • Jiachang Liu, Chudi Zhong, Margo Seltzer, Cynthia Rudin
For fast sparse logistic regression, our computational speed-up over other best-subset search techniques owes to linear and quadratic surrogate cuts for the logistic loss that allow us to efficiently screen features for elimination, as well as use of a priority queue that favors a more uniform exploration of features.
3 code implementations • 1 Dec 2021 • Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo Seltzer
We show that by using these guesses, we can reduce the run time by multiple orders of magnitude, while providing bounds on how far the resulting trees can deviate from the black box's accuracy and expressive power.
no code implementations • 21 May 2021 • Aarti Kashyap, Syed Mubashir Iqbal, Karthik Pattabiraman, Margo Seltzer
These attacks, which we call Ripple False Data Injection Attacks (rfdia), use minimal input perturbations to stealthily change the dnn output.
no code implementations • 26 Aug 2020 • Xueyuan Han, Xiao Yu, Thomas Pasquier, Ding Li, Junghwan Rhee, James Mickens, Margo Seltzer, Haifeng Chen
We introduce SIGL, a new tool for detecting malicious behavior during software installation.
2 code implementations • ICML 2020 • Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo Seltzer
Decision tree optimization is notoriously difficult from a computational perspective but essential for the field of interpretable machine learning.
2 code implementations • NeurIPS 2019 • Xiyang Hu, Cynthia Rudin, Margo Seltzer
Decision tree algorithms have been among the most popular algorithms for interpretable (transparent) machine learning since the early 1980's.
1 code implementation • 18 Aug 2018 • Thomas Pasquier, Xueyuan Han, Thomas Moyer, Adam Bates, Olivier Hermant, David Eyers, Jean Bacon, Margo Seltzer
Identifying the root cause and impact of a system intrusion remains a foundational challenge in computer security.
Cryptography and Security Operating Systems
5 code implementations • 6 Apr 2017 • Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo Seltzer, Cynthia Rudin
We present the design and implementation of a custom discrete optimization technique for building rule lists over a categorical feature space.
7 code implementations • ICML 2017 • Hongyu Yang, Cynthia Rudin, Margo Seltzer
They have a logical structure that is a sequence of IF-THEN rules, identical to a decision list or one-sided decision tree.
no code implementations • 28 Mar 2014 • Elaine Angelino, Eddie Kohler, Amos Waterland, Margo Seltzer, Ryan P. Adams
We present a general framework for accelerating a large class of widely used Markov chain Monte Carlo (MCMC) algorithms.