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Mar 30, 2020
Computer Vision
Machine Learning
Image and Video Processing

In this paper, we proposed a differentiable automatic meta pruning method via hypernetwork for network compression. The differentiability comes with the specially designed hypernetwork and the proximal gradient used to search the potential candidate…

DHP: Differentiable Meta Pruning via HyperNetworks

Network pruning has been the driving force for the efficient inference of neural networks and the alleviation of model storage and transmission burde…
Mar 30, 2020
Computational Physics
Machine Learning

Detecting symmetries in an automated fashion removes the necessity for domain knowledge associated to a particular data product. Such domain knowledge often might not be of existence or has been the outcome of scientific efforts such as in the devel…

Detecting Symmetries with Neural Networks

Identifying symmetries in data sets is generally difficult, but knowledge about them is crucial for efficient data handling. Here we present a method…
Mar 30, 2020
Computer Vision
Machine Learning

In this work, we present a new network design paradigm. Our results suggest that designing network design spaces is a promising avenue for future research.

Designing Network Design Spaces

In this work, we present a new network design paradigm. Our goal is to help advance the understanding of network design and discover design principle…
Mar 27, 2020
Computer Vision

DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search

Efficient search is a core issue in Neural Architecture Search (NAS). It is difficult for conventional NAS algorithms to directly search the architec…
Mar 27, 2020
Computer Vision

Assessing Image Quality Issues for Real-World Problem

We introduce a new large-scale dataset that links the assessment of image quality issues to two practical vision tasks: image captioning and visual q…
Mar 27, 2020
Computer Vision

Hybrid Models for Open Set Recognition

Open set recognition requires a classifier to detect samples not belonging to any of the classes in its training set. Existing methods fit a probabil…
Mar 27, 2020
Machine Learning

ABBA: Adaptive Brownian bridge-based symbolic aggregation of time ser…

A new symbolic representation of time series, called ABBA, is introduced. It is based on an adaptive polygonal chain approximation of the time series…
Mar 27, 2020
Instrumentation and Detectors
Machine Learning

Using Machine Learning to Speed Up and Improve Calorimeter R&D

Design of new experiments, as well as upgrade of ongoing ones, is a continuous process in the experimental high energy physics. Since the best soluti…
Mar 27, 2020
Methodology
Machine Learning

Robust Q-learning

Q-learning is a regression-based approach that is widely used to formalize the development of an optimal dynamic treatment strategy. Finite dimension…
Mar 27, 2020
Audio and Speech Processing
Machine Learning
Sound

Mic2Mic: Using Cycle-Consistent Generative Adversarial Networks to …

Mobile and embedded devices are increasingly using microphones and audio-based computational models to infer user context. A major challenge in build…
Mar 27, 2020
Computer Vision

Weakly-Supervised Action Localization by Generative Attention Modeling

Weakly-supervised temporal action localization is a problem of learning an action localization model with only video-level action labeling available.…
Mar 27, 2020
Machine Learning
Distributed
Parallel
and Cluster Computing
Information Theory
Optimization and Control

A Hybrid-Order Distributed SGD Method for Non-Convex Optimization to …

In this paper, we propose a method of distributed stochastic gradient descent (SGD), with low communication load and computational complexity, and st…
Mar 27, 2020
Machine Learning
Methodology

On the role of surrogates in the efficient estimation of treatment …

We study the problem of estimating treatment effects when the outcome of primary interest (e.g., long-term health status) is only seldom observed but…
Mar 27, 2020
Machine Learning
Numerical Analysis
Optimization and Control

The authors would like to thank Emilie Renard for the stimulating discussions that improved the ideas presented here.

On a minimum enclosing ball of a collection of linear subspaces

This paper concerns the minimax center of a collection of linear subspaces. When the subspaces are $k$-dimensional subspaces of $\mathbb{R}^n$, this …
Mar 27, 2020
Computation and Language

The quality of sentiment labels generated by our updated VADER lexicon is better compared to the labels generated by the original VADER English lexicon.1.Sentiment labels by human annotators was able to capture nuances that the rule based sentiment …

Semantic Enrichment of Nigerian Pidgin English for Contextual Sentime…

Nigerian English adaptation, Pidgin, has evolved over the years through multi-language code switching, code mixing and linguistic adaptation. While P…
Mar 27, 2020
Computer Vision

We proposed conditional implicit surface light fields, a novel representation of visual appearance of 3D objects. Our model reasons about complex visual effects including texture, diffuse and specular reflection as well as shadows. Our representatio…

Learning Implicit Surface Light Fields

Implicit representations of 3D objects have recently achieved impressive results on learning-based 3D reconstruction tasks. While existing works use …
Mar 27, 2020
Machine Learning
Computer Vision

MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Refor…

Many recently proposed methods for Neural Architecture Search (NAS) can be formulated as bilevel optimization. For efficient implementation, its solu…
Mar 27, 2020
Computer Vision

Towards Discriminability and Diversity: Batch Nuclear-norm Maximizati…

The learning of the deep networks largely relies on the data with human-annotated labels. In some label insufficient situations, the performance degr…
Mar 27, 2020
Computer Vision

Learning to Optimize Non-Rigid Tracking

One of the widespread solutions for non-rigid tracking has a nested-loop structure: with Gauss-Newton to minimize a tracking objective in the outer l…
Mar 27, 2020
Computer Vision

Multi-Granularity Reference-Aided Attentive Feature Aggregation for …

Video-based person re-identification (reID) aims at matching the same person across video clips. It is a challenging task due to the existence of red…
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