Richard S. Zemel
18 papers · 2006–2023 · 5 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (9) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (19) π£ Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(19)
π
Conference Polyglot
(5)
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(7)
π
Keyword Champion
ποΈ
Keyword Collector
(52)
π
Century Club
(18)
π
Trend Setter
π
Conference Pioneer
β
The Questioner
Conferences
NIPS (12)
CVPR (2)
JMLR (2)
ICLR (1)
ICML (1)
Top co-authors
Keywords
generative model
(3)
representation learning
(3)
collaborative filtering
(2)
neural network
(2)
image annotation
(2)
matrix factorization
(2)
probabilistic modeling
(2)
learning to rank
(2)
restricted boltzmann machine
(2)
discriminative model
(2)
probabilistic model
(2)
metric learning
(2)
bayesian inference
(1)
risk management
(1)
feature extraction
(1)
variational inference
(1)
algorithmic fairness
(1)
semantic segmentation
(1)
spectral clustering
(1)
uncertainty quantification
(1)
Papers
Distribution-Free Statistical Dispersion Control for Societal Applications
NIPS 2023
Implications of Model Indeterminacy for Explanations of Automated Decisions
NIPS 2022
Deep Ensembles Work, But Are They Necessary?
NIPS 2022
Identifying and Benchmarking Natural Out-of-Context Prediction Problems
NIPS 2021
Variational Model Inversion Attacks
NIPS 2021
Meta-Learning for Semi-Supervised Few-Shot Classification
ICLR 2018
End-To-End Instance Segmentation With Recurrent Attention
CVPR 2017
Deep Spectral Clustering Learning
ICML 2017
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data
CVPR 2017
New Learning Methods for Supervised and Unsupervised Preference Aggregation
JMLR 2014
Probabilistic n-Choose-k Models for Classification and Ranking
NIPS 2012
Efficient Sampling for Bipartite Matching Problems
NIPS 2012
Cardinality Restricted Boltzmann Machines
NIPS 2012
Collaborative Ranking With 17 Parameters
NIPS 2012
Characterizing response behavior in multisensory perception with conflicting cues
NIPS 2008
Learning Hybrid Models for Image Annotation with Partially Labeled Data
NIPS 2008
Generative versus discriminative training of RBMs for classification of fMRI images
NIPS 2008
Learning Parts-Based Representations of Data
JMLR 2006