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Testing the Genomic Bottleneck Hypothesis in Hebbian Meta-Learning


Authors:  RasmusBergPalm, EliasNajarro, SebastianRisi....
Published date-11/13/2020
Tasks:  Meta-Learning

Abstract: Recent work has shown promising results using Hebbian meta-learning to solve hard reinforcement learning problems and adapt-to a limited degree-to changes in the environment. In previous works each synapse has …

Interpretable Multi-dataset Evaluation for Named Entity Recognition


Authors:  JinlanFu, PengFeiLiu, GrahamNeubig....
Published date-11/13/2020
Tasks:  NamedEntityRecognition

Abstract: With the proliferation of models for natural language processing tasks, it is even harder to understand the differences between models and their relative merits. Simply looking at differences between holistic …

ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning


Authors:  YuFeiWang, GauthamNarayanNarasimhan, XingyuLin....
Published date-11/13/2020
Tasks:  Multi-GoalReinforcementLearning

Abstract: Current image-based reinforcement learning (RL) algorithms typically operate on the whole image without performing object-level reasoning. This leads to inefficient goal sampling and ineffective reward functions. In this paper, we …

Gaussian RAM: Lightweight Image Classification via Stochastic Retina-Inspired Glimpse and Reinforcement Learning


Authors:  DongseokShim, H.JinKim....
Published date-11/12/2020
Tasks:  ImageClassification, ModelCompression

Abstract: Previous studies on image classification have mainly focused on the performance of the networks, not on real-time operation or model compression. We propose a Gaussian Deep Recurrent visual Attention Model …

Hierarchical Prosody Modeling for Non-Autoregressive Speech Synthesis


Authors:  Chung-MingChien, Hung-YiLee....
Published date-11/12/2020
Tasks:  SpeechSynthesis

Abstract: Prosody modeling is an essential component in modern text-to-speech (TTS) frameworks. By explicitly providing prosody features to the TTS model, the style of synthesized utterances can thus be controlled. However, …

Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Grasping


Authors:  AdithyavairavanMurali, WeiyuLiu, KennethMarino....
Published date-11/12/2020
Tasks:  RoboticGrasping

Abstract: Despite the enormous progress and generalization in robotic grasping in recent years, existing methods have yet to scale and generalize task-oriented grasping to the same extent. This is largely due …

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