
On the Sample Complexity of Rank Regression from Pairwise Comparisons
We consider a rank regression setting, in which a dataset of N samples w...
read it

Machine Learning on Camera Images for Fast mmWave Beamforming
Perfect alignment in chosen beam sectors at both transmit and receiven...
read it

OpenWorld Class Discovery with Kernel Networks
We study an OpenWorld Class Discovery problem in which, given labeled t...
read it

LearnPruneShare for Lifelong Learning
In lifelong learning, we wish to maintain and update a model (e.g., a ne...
read it

Kernel Dependence Network
We propose a greedy strategy to spectrally train a deep network for mult...
read it

Using Undersampling with Ensemble Learning to Identify Factors Contributing to Preterm Birth
In this paper, we propose Ensemble Learning models to identify factors c...
read it

Layerwise Learning of Kernel Dependence Networks
We propose a greedy strategy to train a deep network for multiclass cla...
read it

Deep Markov SpatioTemporal Factorization
We introduce deep Markov spatiotemporal factorization (DMSTF), a deep g...
read it

Weighting Is Worth the Wait: Bayesian Optimization with Importance Sampling
Many contemporary machine learning models require extensive tuning of hy...
read it

Segmentation of Cellular Patterns in Confocal Images of Melanocytic Lesions in vivo via a Multiscale EncoderDecoder Network (MEDNet)
Invivo optical microscopy is advancing into routine clinical practice f...
read it

Spectral NonConvex Optimization for Dimension Reduction with HilbertSchmidt Independence Criterion
The Hilbert Schmidt Independence Criterion (HSIC) is a kernel dependence...
read it

Solving Interpretable Kernel Dimension Reduction
Kernel dimensionality reduction (KDR) algorithms find a low dimensional ...
read it

Deep Kernel Learning for Clustering
We propose a deep learning approach for discovering kernels tailored to ...
read it

Neural Topographic Factor Analysis for fMRI Data
Neuroimaging experiments produce a large volume (gigabytes) of highdime...
read it

Accelerated Experimental Design for Pairwise Comparisons
Pairwise comparison labels are more informative and less variable than c...
read it

Deep feature transfer between localization and segmentation tasks
In this paper, we propose a new pretraining scheme for Unet based imag...
read it

Quantifying Uncertainty in DiscreteContinuous and Skewed Data with Bayesian Deep Learning
Deep Learning (DL) methods have been transforming computer vision with i...
read it

Modeling Multiple Annotator Expertise in the SemiSupervised Learning Scenario
Learning algorithms normally assume that there is at most one annotation...
read it
Jennifer Dy
is this you? claim profile