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Found 12 papers, 8 papers with code
A Statistical Guarantee for Representation Transfer in Multitask Imitation Learning
Transferring representation for multitask imitation learning has the potential to provide improved sample efficiency on learning new tasks, when compared to learning from scratch.
Active Perception and Representation for Robotic Manipulation
It also enables them to view objects from different distances and viewpoints, providing a rich visual experience from which to learn abstract representations of the environment.
Autoregressive Policies for Continuous Control Deep Reinforcement Learning
We introduce a family of stationary autoregressive (AR) stochastic processes to facilitate exploration in continuous control domains.
Benchmarking Reinforcement Learning Algorithms on Real-World Robots
The research community is now able to reproduce, analyze and build quickly on these results due to open source implementations of learning algorithms and simulated benchmark tasks.
Setting up a Reinforcement Learning Task with a Real-World Robot
Reinforcement learning is a promising approach to developing hard-to-engineer adaptive solutions for complex and diverse robotic tasks.
Theano: A Python framework for fast computation of mathematical expressions
Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements.
Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn
Hyperopt-sklearn is a new software project that provides automatic algorithm configuration of the Scikit-learn machine learning library.
Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms
Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization.
Challenges in Representation Learning: A report on three machine learning contests
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge.
Ranked #12 on
Facial Expression Recognition (FER)
on FER2013
Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be?
This paper also introduces a new ensemble construction variant that combines hyperparameter optimization with the construction of ensembles.
Facial Expression Recognition
Facial Expression Recognition (FER)
+2
Theano: new features and speed improvements
Theano is a linear algebra compiler that optimizes a user's symbolically-specified mathematical computations to produce efficient low-level implementations.
