ICML 2018

Hierarchical Text Generation and Planning for Strategic Dialogue

ICML 2018 facebookresearch/end-to-end-negotiator

End-to-end models for goal-orientated dialogue are challenging to train, because linguistic and strategic aspects are entangled in latent state vectors.

DECISION MAKING

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

ICML 2018 deepmind/scalable_agent

In this work we aim to solve a large collection of tasks using a single reinforcement learning agent with a single set of parameters.

ATARI GAMES

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

ICML 2018 anishathalye/obfuscated-gradients

We identify obfuscated gradients, a kind of gradient masking, as a phenomenon that leads to a false sense of security in defenses against adversarial examples.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

Adversarially Regularized Autoencoders

ICML 2018 jakezhaojb/ARAE

This adversarially regularized autoencoder (ARAE) allows us to generate natural textual outputs as well as perform manipulations in the latent space to induce change in the output space.

REPRESENTATION LEARNING STYLE TRANSFER

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

ICML 2018 haarnoja/sac

Model-free deep reinforcement learning (RL) algorithms have been demonstrated on a range of challenging decision making and control tasks.

CONTINUOUS CONTROL DECISION MAKING Q-LEARNING

Addressing Function Approximation Error in Actor-Critic Methods

ICML 2018 sfujim/TD3

In value-based reinforcement learning methods such as deep Q-learning, function approximation errors are known to lead to overestimated value estimates and suboptimal policies.

Q-LEARNING

Learning Representations and Generative Models for 3D Point Clouds

ICML 2018 optas/latent_3d_points

Three-dimensional geometric data offer an excellent domain for studying representation learning and generative modeling.

REPRESENTATION LEARNING

Provable defenses against adversarial examples via the convex outer adversarial polytope

ICML 2018 locuslab/convex_adversarial

We propose a method to learn deep ReLU-based classifiers that are provably robust against norm-bounded adversarial perturbations on the training data.

ADVERSARIAL ATTACK

Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron

ICML 2018 syang1993/gst-tacotron

We present an extension to the Tacotron speech synthesis architecture that learns a latent embedding space of prosody, derived from a reference acoustic representation containing the desired prosody.

SPEECH SYNTHESIS