research
∙
07/16/2023
A max-affine spline approximation of neural networks using the Legendre transform of a convex-concave representation
This work presents a novel algorithm for transforming a neural network i...
share
research
∙
02/28/2023
Tiny Classifier Circuits: Evolving Accelerators for Tabular Data
A typical machine learning (ML) development cycle for edge computing is ...
research
∙
01/10/2023
A Unified Theory of Diversity in Ensemble Learning
We present a theory of ensemble diversity, explaining the nature and eff...
research
∙
07/15/2022
Outlier detection of vital sign trajectories from COVID-19 patients
There is growing interest in continuous wearable vital sign sensors for ...
research
∙
06/09/2022
Strong Memory Lower Bounds for Learning Natural Models
We give lower bounds on the amount of memory required by one-pass stream...
research
∙
04/26/2022
Bias-Variance Decompositions for Margin Losses
We introduce a novel bias-variance decomposition for a range of strictly...
research
∙
06/24/2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation
We present two sample-efficient differentially private mean estimators f...
research
∙
12/11/2020
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?
Modern machine learning models are complex and frequently encode surpris...
research
∙
11/08/2020
Performative Prediction in a Stateful World
Deployed supervised machine learning models make predictions that intera...
research
∙
10/15/2020
Ensembles of Spiking Neural Networks
This paper demonstrates that ensembles of spiking neural networks can be...
research
∙
01/28/2020
Margin Maximization as Lossless Maximal Compression
The ultimate goal of a supervised learning algorithm is to produce model...
research
∙
01/16/2020
Better Boosting with Bandits for Online Learning
Probability estimates generated by boosting ensembles are poorly calibra...
research
∙
02/12/2019
Joint Training of Neural Network Ensembles
We examine the practice of joint training for neural network ensembles, ...
research
∙
04/21/2018
Is feature selection secure against training data poisoning?
Learning in adversarial settings is becoming an important task for appli...
research
∙
03/01/2018
The K-Nearest Neighbour UCB algorithm for multi-armed bandits with covariates
In this paper we propose and explore the k-Nearest Neighbour UCB algorit...
research
∙
03/01/2018
Diversity and degrees of freedom in regression ensembles
Ensemble methods are a cornerstone of modern machine learning. The perfo...
research
∙
03/01/2018
Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours
We study the approximate nearest neighbour method for cost-sensitive cla...
research
∙
08/23/2017