Jennifer Dy
38 papers · 2010–2026 · 13 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+12 more ↓ Show less ↑
π£ Hot Topic Early Bird π§ Keyword Pioneer π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (16) π Conference Polyglot (13)
π
Academic Marathon
(16)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π¬
Deep Specialist
(10)
π§¬
Topic Evolution
π€
Dynamic Duo
(11)
ποΈ
Keyword Collector
(160)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(38)
π₯
Unstoppable
(11)
Conferences
AISTATS (17)
NIPS (7)
ACML (2)
ICLR (2)
ICML (2)
ACL (1)
CVPR (1)
ECCV (1)
EMNLP (1)
IJCAI (1)
JMLR (1)
MLHC (1)
WACV (1)
Top co-authors
Keywords
alternating direction method of multiplier
(4)
mutual information
(4)
variational inference
(3)
continual learning
(3)
catastrophic forgetting
(3)
plackett-luce model
(3)
feature attribution
(2)
active learning
(2)
probabilistic model
(2)
multi-annotator learning
(2)
spectral algorithm
(2)
gaussian process
(2)
spectral clustering
(2)
nonparametric bayesian
(2)
dimensionality reduction
(2)
feature selection
(2)
black-box optimization
(1)
dirichlet process
(1)
adversarial robustness
(1)
iterative optimization
(1)
Papers
SSplain: Sparse and Smooth Explainer for Retinopathy of Prematurity Classification
WACV 2026
STAR: Stability-Inducing Weight Perturbation for Continual Learning
ICLR 2025
Axiomatic Explainer Globalness via Optimal Transport
AISTATS 2025
Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation
EMNLP 2025
Boundary-Aware Uncertainty for Feature Attribution Explainers
AISTATS 2024
Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions
AISTATS 2024
DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning
ICML 2023
SmoothHess: ReLU Network Feature Interactions via Stein's Lemma
NIPS 2023
QueryForm: A Simple Zero-shot Form Entity Query Framework
ACL 2023
Deep Layer-wise Networks Have Closed-Form Weights
AISTATS 2022
SparCL: Sparse Continual Learning on the Edge
NIPS 2022
Explanations of Black-Box Models based on Directional Feature Interactions
ICLR 2022
DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning
ECCV 2022
Learning To Prompt for Continual Learning
CVPR 2022
Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling
AISTATS 2021
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness
NIPS 2021
Rate-Regularization and Generalization in Variational Autoencoders
AISTATS 2021
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space
NIPS 2021
Deep Spectral Ranking
AISTATS 2021
Fast and Accurate Ranking Regression
AISTATS 2020
Neural Topographic Factor Analysis for fMRI Data
NIPS 2020
Instance-wise Feature Grouping
NIPS 2020
Structured Disentangled Representations
AISTATS 2019
Solving Interpretable Kernel Dimensionality Reduction
NIPS 2019
ADMMBO: Bayesian Optimization with Unknown Constraints using ADMM
JMLR 2019
Variational Inference from Ranked Samples with Features
ACML 2019
Iterative Spectral Method for Alternative Clustering
AISTATS 2018
Crowdclustering with Partition Labels
AISTATS 2018
Experimental Design under the Bradley-Terry Model
IJCAI 2018
Rate Optimal Estimation for High Dimensional Spatial Covariance Matrices
ACML 2017
Clustering from Multiple Uncertain Experts
AISTATS 2017
Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy
MLHC 2016
A Robust-Equitable Copula Dependence Measure for Feature Selection
AISTATS 2016
Nonparametric Mixture of Gaussian Processes with Constraints
ICML 2013
A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views
AISTATS 2012
Active Learning from Multiple Knowledge Sources
AISTATS 2012
Dimensionality Reduction for Spectral Clustering
AISTATS 2011
Modeling annotator expertise: Learning when everybody knows a bit of something
AISTATS 2010