Nando Freitas
12 papers · 2005–2017 · 3 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
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πΊοΈ Taxonomy Completionist (21) π Academic Marathon Β· Half π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π§
Keyword Pioneer
ποΈ
Keyword Collector
(52)
π
Trend Setter
π
Century Club Β· Bronze
π
Conference Pioneer
π
Renaissance Researcher
(5)
Venues
Top co-authors
Research topics
Machine Learning
(10)
Optimization & Theory
(9)
Artificial Intelligence
(4)
Deep Learning
(4)
Mathematics & Optimization
(2)
Reinforcement Learning
(2)
Architectures
(2)
Bayesian & Probabilistic
(2)
Learning Paradigms
(2)
Learning Types Β· Machine Learning
(2)
Learning Types Β· Deep Learning
(2)
Methods
(2)
Models
(2)
Optimization
(2)
Computer Vision
(1)
Keywords
bayesian optimization
(5)
gradient descent
(2)
hyperparameter tuning
(2)
global optimization
(2)
online learning
(1)
black-box optimization
(1)
stochastic gradient descent
(1)
video generation
(1)
image generation
(1)
adaptive sampling
(1)
markov chain monte carlo
(1)
maximum likelihood
(1)
gaussian process
(1)
policy gradient
(1)
partition function
(1)
density estimation
(1)
continuous control
(1)
mcmc sampling
(1)
value function estimation
(1)
multi-task learning
(1)
Papers
Learned Optimizers that Scale and Generalize
ICML 2017
Learning to Learn without Gradient Descent by Gradient Descent
ICML 2017
Parallel Multiscale Autoregressive Density Estimation
ICML 2017
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously
CoRL 2017
Dueling Network Architectures for Deep Reinforcement Learning
ICML 2016
Unbounded Bayesian Optimization via Regularization
AISTATS 2016
Bayesian Multi-Scale Optimistic Optimization
AISTATS 2014
On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning
AISTATS 2014
Adaptive Hamiltonian and Riemann Manifold Monte Carlo
ICML 2013
Consistency of Online Random Forests
ICML 2013
Inductive Principles for Restricted Boltzmann Machine Learning
AISTATS 2010
An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward
AISTATS 2005