Misha Denil
20 papers · 2013–2024 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+9 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (45) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π±
Topic Pioneer
π€
Dynamic Duo
(13)
π§
Keyword Pioneer
π
Renaissance Researcher
(6)
π₯
Unstoppable Β· Bronze
π
Conference Pioneer
π
Century Club Β· Bronze
π
Trend Setter
ποΈ
Keyword Collector
(98)
Top co-authors
Research topics
Machine Learning
(15)
Artificial Intelligence
(10)
Optimization & Theory
(8)
Deep Learning
(7)
Core AI
(7)
Reinforcement Learning
(6)
Learning Types
(6)
Architectures
(5)
Core Methods
(5)
Methods
(5)
Learning Paradigms
(4)
Applications
(3)
Mathematics & Optimization
(2)
Bayesian & Probabilistic
(2)
Techniques
(2)
Keywords
reinforcement learning
(3)
gradient descent
(3)
model compression
(2)
reward learning
(2)
graphical model
(2)
bayesian optimization
(2)
neural network optimization
(2)
markov random field
(2)
random forest
(2)
reward modeling
(1)
robotic manipulation
(1)
policy optimization
(1)
black-box optimization
(1)
policy gradient
(1)
off-policy evaluation
(1)
representation learning
(1)
imitation learning
(1)
neural machine translation
(1)
probabilistic modeling
(1)
attention mechanism
(1)
Papers
Ο2vec: Policy Representation with Successor Features
ICLR 2024
Active Offline Policy Selection
NeurIPS 2021
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
ICLR 2020
Positive-Unlabeled Reward Learning
CoRL 2020
Scaling data-driven robotics with reward sketching and batch reinforcement learning
RSS 2020
Task-Relevant Adversarial Imitation Learning
CoRL 2020
Hyperbolic Attention Networks
ICLR 2019
Large-Scale Visual Speech Recognition
Interspeech 2019
Learning Awareness Models
ICLR 2018
Learned Optimizers that Scale and Generalize
ICML 2017
Learning to Learn without Gradient Descent by Gradient Descent
ICML 2017
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously
CoRL 2017
Learning to learn by gradient descent by gradient descent
NeurIPS 2016
Noisy Activation Functions
ICML 2016
Deep Fried Convnets
ICCV 2015
Distributed Parameter Estimation in Probabilistic Graphical Models
NeurIPS 2014
Linear and Parallel Learning of Markov Random Fields
ICML 2014
Narrowing the Gap: Random Forests In Theory and In Practice
ICML 2014
Consistency of Online Random Forests
ICML 2013
Predicting Parameters in Deep Learning
NeurIPS 2013