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Oct 22, 2020
Machine Learning
Artificial Intelligence
Robotics

Accelerating Reinforcement Learning with Learned Skill Priors

Intelligent agents rely heavily on prior experience when learning a new task, yet most modern reinforcement learning (RL) approaches learn every task…
Oct 22, 2020
Robotics
Artificial Intelligence
Machine Learning

Motion Planner Augmented Reinforcement Learning for Robot Manipulatio…

Deep reinforcement learning (RL) agents are able to learn contact-rich manipulation tasks by maximizing a reward signal, but require large amounts of…
Oct 22, 2020
Machine Learning
Computation and Language

Autoregressive Modeling is Misspecified for Some Sequence Distributio…

Should sequences be modeled autoregressively---one symbol at a time? How much computation is needed to predict the next symbol? While local normaliza…
Oct 22, 2020
Computation and Language
Artificial Intelligence

UniCase -- Rethinking Casing in Language Models

In this paper, we introduce a new approach to dealing with the problem of case-sensitiveness in Language Modelling (LM). We propose simple architectu…
Oct 22, 2020
Computation and Language

mT5: A massively multilingual pre-trained text-to-text transformer

The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified text-to-text format and scale to attain state-of-the-art results on a wide va…
Oct 22, 2020
Robotics

Minimal Exposure Dubins Orienteering Problem

Different applications, such as environmental monitoring and military operations, demand the observation of predefined target locations, and an auton…
Oct 22, 2020
Neural and Evolutionary Computation
Machine Learning

Brain-Inspired Learning on Neuromorphic Substrates

Neuromorphic hardware strives to emulate brain-like neural networks and thus holds the promise for scalable, low-power information processing on temp…
Oct 22, 2020
Computation and Language
Information Retrieval

Scientific Claim Verification with VERT5ERINI

This work describes the adaptation of a pretrained sequence-to-sequence model to the task of scientific claim verification in the biomedical domain. …
Oct 22, 2020
Computer Vision
Artificial Intelligence
Machine Learning

An Image is Worth 16x16 Words: Transformers for Image Recognition at …

While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain…
Oct 22, 2020
Artificial Intelligence
Machine Learning

Neural-Symbolic Integration: A Compositional Perspective

Despite significant progress in the development of neural-symbolic frameworks, the question of how to integrate a neural and a symbolic system in a \…
Oct 22, 2020
Machine Learning

In Search of Robust Measures of Generalization

One of the principal scientific challenges in deep learning is explaining generalization, i.e., why the particular way the community now trains netwo…
Oct 22, 2020
Machine Learning
Computation and Language

AdapterDrop: On the Efficiency of Adapters in Transformers

Massively pre-trained transformer models are computationally expensive to fine-tune, slow for inference, and have large storage requirements. Recent …
Oct 22, 2020
Robotics
Artificial Intelligence
Machine Learning

Batch Exploration with Examples for Scalable Robotic Reinforcement …

Learning from diverse offline datasets is a promising path towards learning general purpose robotic agents. However, a core challenge in this paradig…
Oct 22, 2020
Robotics
Signal Processing

Source localization using particle filtering on FPGA for robotic na…

Particle filtering is a recursive Bayesian estimation technique that has gained popularity recently for tracking and localization applications. It us…
Oct 22, 2020
Sound
Information Retrieval
Machine Learning
Audio and Speech Processing

Neural Audio Fingerprint for High-specific Audio Retrieval based on …

Most of existing audio fingerprinting systems have limitations to be used for high-specific audio retrieval at scale. In this work, we generate a low…
Oct 22, 2020
Signal Processing
Information Theory
Machine Learning

Contrastive Self-Supervised Learning for Wireless Power Control

We propose a new approach for power control in wireless networks using self-supervised learning. We partition a multi-layer perceptron that takes as …
Oct 22, 2020
Sound
Machine Learning
Audio and Speech Processing

Transcription Is All You Need: Learning to Separate Musical Mixtures …

Most music source separation systems require large collections of isolated sources for training, which can be difficult to obtain. In this work, we u…
Oct 22, 2020
Machine Learning
Artificial Intelligence
Optimization and Control

What are the Statistical Limits of Offline RL with Linear Function …

Offline reinforcement learning seeks to utilize offline (observational) data to guide the learning of (causal) sequential decision making strategies.…
Oct 22, 2020
Computation and Language
Artificial Intelligence
Machine Learning

Self-alignment Pre-training for Biomedical Entity Representations

Despite the widespread success of self-supervised learning via masked language models, learning representations directly from text to accurately capt…
Oct 22, 2020
Data Structures and Algorithms
Machine Learning

In addition to CSQ lower bounds, [MS20] also prove hardness of approximation results for a family in terms of its correlational variance. Given a hypothesis class H and a family A of function-distribution pairs, a hardness of approximation result ta…

The Polynomial Method is Universal for Distribution-Free Correlationa…

We consider the problem of distribution-free learning for Boolean function classes in the PAC and agnostic models. Generalizing a recent beautiful wo…
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