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07/07/2023
A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearables
Smart watches and other wearable devices are equipped with photoplethysm...
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07/06/2023
Learned Kernels for Interpretable and Efficient PPG Signal Quality Assessment and Artifact Segmentation
Photoplethysmography (PPG) provides a low-cost, non-invasive method to c...
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07/04/2023
A Double Machine Learning Approach to Combining Experimental and Observational Data
Experimental and observational studies often lack validity due to untest...
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04/23/2023
Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?
Missing values are a fundamental problem in data science. Many datasets ...
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04/13/2023
OKRidge: Scalable Optimal k-Sparse Ridge Regression for Learning Dynamical Systems
We consider an important problem in scientific discovery, identifying sp...
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04/03/2023
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics
We introduce Matched Machine Learning, a framework that combines the fle...
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03/28/2023
Understanding and Exploring the Whole Set of Good Sparse Generalized Additive Models
In real applications, interaction between machine learning model and dom...
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02/23/2023
From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference
Our goal is to produce methods for observational causal inference that a...
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11/09/2022
Mapping the Ictal-Interictal-Injury Continuum Using Interpretable Machine Learning
IMPORTANCE: An interpretable machine learning model can provide faithful...
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10/13/2022
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design
Sparse decision trees are one of the most common forms of interpretable ...
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10/12/2022
FasterRisk: Fast and Accurate Interpretable Risk Scores
Over the last century, risk scores have been the most popular form of pr...
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09/19/2022
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization
Given thousands of equally accurate machine learning (ML) models, how ca...
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09/16/2022
Exploring the Whole Rashomon Set of Sparse Decision Trees
In any given machine learning problem, there may be many models that cou...
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06/09/2022
There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes
Interpretability is an essential building block for trustworthiness in r...
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04/22/2022
SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation
Visual concept discovery has long been deemed important to improve inter...
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03/09/2022
Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It
Many fundamental problems affecting the care of critically ill patients ...
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02/23/2022
Fast Sparse Classification for Generalized Linear and Additive Models
We present fast classification techniques for sparse generalized linear ...
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12/01/2021
How Smart Guessing Strategies Can Yield Massive Scalability Improvements for Sparse Decision Tree Optimization
Sparse decision tree optimization has been one of the most fundamental p...
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11/10/2021
How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning
Metamaterials are composite materials with engineered geometrical micro-...
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09/15/2021
BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales
Algorithmic harmonization - the automated harmonization of a musical pie...
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07/12/2021
Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning
When we deploy machine learning models in high-stakes medical settings, ...
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06/24/2021
Multitask Learning for Citation Purpose Classification
We present our entry into the 2021 3C Shared Task Citation Context Class...
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06/04/2021
A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations
Lending decisions are usually made with proprietary models that provide ...
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05/12/2021
Playing Codenames with Language Graphs and Word Embeddings
Although board games and video games have been studied for decades in ar...
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04/30/2021
Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization
AI has the potential to revolutionize many areas of healthcare. Radiolog...
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03/23/2021
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography
Interpretability in machine learning models is important in high-stakes ...
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03/20/2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges
Interpretability in machine learning (ML) is crucial for high stakes dec...
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01/06/2021
dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference
dame-flame is a Python package for performing matching for observational...
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12/08/2020
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMAP have...
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11/22/2020
Cryo-ZSSR: multiple-image super-resolution based on deep internal learning
Single-particle cryo-electron microscopy (cryo-EM) is an emerging imagin...
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09/06/2020
Matching Bounds: How Choice of Matching Algorithm Impacts Treatment Effects Estimates and What to Do about It
Different matches on the same data may produce different treatment effec...
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07/17/2020
Bandits for BMO Functions
We study the bandit problem where the underlying expected reward is a Bo...
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06/15/2020
Generalized Optimal Sparse Decision Trees
Decision tree optimization is notoriously difficult from a computational...
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05/08/2020
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction
In recent years, academics and investigative journalists have criticized...
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03/08/2020
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
The primary aim of single-image super-resolution is to construct a high-...
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03/03/2020
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation
We propose a matching method for observational data that matches units w...
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03/02/2020
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference
We propose a matching method that recovers direct treatment effects from...
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02/05/2020
Concept Whitening for Interpretable Image Recognition
What does a neural network encode about a concept as we traverse through...
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08/05/2019
A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning
The Rashomon effect occurs when many different explanations exist for th...
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07/04/2019
Reducing Exploration of Dying Arms in Mortal Bandits
Mortal bandits have proven to be extremely useful for providing news art...
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06/27/2019
Interpretable Almost-Matching-Exactly With Instrumental Variables
Uncertainty in the estimation of the causal effect in observational stud...
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06/25/2019
Interpretable Image Recognition with Hierarchical Prototypes
Vision models are interpretable when they classify objects on the basis ...
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06/04/2019
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis
Despite the widespread usage of machine learning throughout organization...
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04/29/2019
Optimal Sparse Decision Trees
Decision tree algorithms have been among the most popular algorithms for...
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01/26/2019
A Practical Bandit Method with Advantages in Neural Network Tuning
Stochastic bandit algorithms can be used for challenging non-convex opti...
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01/10/2019
Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models
Variable importance is central to scientific studies, including the soci...
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12/05/2018
Hypothesis Tests That Are Robust to Choice of Matching Method
A vast number of causal inference studies test hypotheses on treatment e...
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11/30/2018
An Interpretable Model with Globally Consistent Explanations for Credit Risk
We propose a possible solution to a public challenge posed by the Fair I...
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11/26/2018
Please Stop Explaining Black Box Models for High Stakes Decisions
There are black box models now being used for high stakes decision-makin...
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11/18/2018