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Feb 17, 2020
Computer Vision
Machine Learning

Precision Gating: Improving Neural Network Efficiency with Dynamic …

We propose precision gating (PG), an end-to-end trainable dynamic dual-precision quantization technique for deep neural networks. PG computes most fe…
Feb 17, 2020
Image and Video Processing
Computer Vision
Optics

Seeing Around Corners with Edge-Resolved Transient Imaging

Non-line-of-sight (NLOS) imaging is a rapidly growing field seeking to form images of objects outside the field of view, with potential applications …
Feb 17, 2020
Machine Learning
Artificial Intelligence

Handling Missing Annotations in Supervised Learning Data

Data annotation is an essential stage in supervised learning. However, the annotation process is exhaustive and time consuming, specially for large d…
Feb 17, 2020
Artificial Intelligence

Targeted Forgetting and False Memory Formation in Continual Learners …

Artificial neural networks are well-known to be susceptible to catastrophic forgetting when continually learning from sequences of tasks. Various con…
Feb 17, 2020
Machine Learning
Artificial Intelligence
Computation and Language

Controlling Computation versus Quality for Neural Sequence Models

Most neural networks utilize the same amount of compute for every example independent of the inherent complexity of the input. Further, methods that …
Feb 17, 2020
Machine Learning
Artificial Intelligence

Augmented Normalizing Flows: Bridging the Gap Between Generative Flow…

In this work, we propose a new family of generative flows on an augmented data space, with an aim to improve expressivity without drastically increas…
Feb 17, 2020
Image and Video Processing
Artificial Intelligence
Machine Learning

4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anat…

We propose a hybrid controllable image generation method to synthesize anatomically meaningful 3D+t labeled Cardiac Magnetic Resonance (CMR) images. …
Feb 17, 2020
Cryptography and Security
Computer Vision
Machine Learning

Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual …

We present Survival-OPT, a physical adversarial example algorithm in the black-box hard-label setting where the attacker only has access to the model…
Feb 17, 2020
Machine Learning

In this work, we proposed subset sampling and online hyper-parameter selection to speed up and enhance PNNL algorithms. Empirical results demonstrated with PMLP show that proposed approach can not only accelerate the optimization procedure in PMLP b…

Subset Sampling For Progressive Neural Network Learning

Progressive Neural Network Learning is a class of algorithms that incrementally construct the network's topology and optimize its parameters based on…
Feb 17, 2020
Machine Learning
Artificial Intelligence
Optimization and Control

In this paper, we propose a novel provably efficient recursion-based algorithm for agnostic Q-learning with general function approximation with bounded Eluder dimension in deterministic systems. We obtain a sharp characterization on the relation bet…

Agnostic Q-learning with Function Approximation in Deterministic Sy…

The current paper studies the problem of agnostic $Q$-learning with function approximation in deterministic systems where the optimal $Q$-function is…
Feb 17, 2020
Image and Video Processing
Machine Learning

Automatic Frame Selection using CNN in Ultrasound Elastography

Ultrasound elastography is used to estimate the mechanical properties of the tissue by monitoring its response to an internal or external force. Diff…
Feb 17, 2020
Machine Learning

Reward Design for Driver Repositioning Using Multi-Agent Reinforcemen…

A large portion of the passenger requests is reportedly unserviced, partially due to vacant for-hire drivers' cruising behavior during the passenger …
Feb 17, 2020
Robotics

Reliable Trajectories for Dynamic Quadrupeds using Analytical Costs a…

Dynamic traversal of uneven terrain is a major objective in the field of legged robotics. The most recent model predictive control approaches for the…
Feb 17, 2020
Machine Learning
Data Analysis
Statistics and Probability

Predicting trends in the quality of state-of-the-art neural networks …

In many applications, one works with deep neural network (DNN) models trained by someone else. For such pretrained models, one typically does not hav…
Feb 17, 2020
Machine Learning
Artificial Intelligence

BatchEnsemble: an Alternative Approach to Efficient Ensemble and Li…

Ensembles, where multiple neural networks are trained individually and their predictions are averaged, have been shown to be widely successful for im…
Feb 17, 2020
Machine Learning
Artificial Intelligence

Investigating Simple Object Representations in Model-Free Deep Rein…

We explore the benefits of augmenting state-of-the-art model-free deep reinforcement algorithms with simple object representations. Following the Fro…
Feb 17, 2020
Computation and Language
Computer Vision
Machine Learning
Neural and Evolutionary Computation

Gaussian Smoothen Semantic Features (GSSF) -- Exploring the Linguisti…

In this work, we have introduced Gaussian Smoothen Semantic Features (GSSF) for Better Semantic Selection for Indian regional language-based image ca…
Feb 17, 2020
Machine Learning
Optimization and Control
Statistics Theory

Structures of Spurious Local Minima in $k$-means

$k$-means clustering is a fundamental problem in unsupervised learning. The problem concerns finding a partition of the data points into $k$ clusters…
Feb 17, 2020
Social and Information Networks
Machine Learning

Global and Local Feature Learning for Ego-Network Analysis

In an ego-network, an individual (ego) organizes its friends (alters) in different groups (social circles). This social network can be efficiently an…
Feb 17, 2020
Multiagent Systems
Artificial Intelligence

R-MADDPG for Partially Observable Environments and Limited Communicat…

There are several real-world tasks that would ben-efit from applying multiagent reinforcement learn-ing (MARL) algorithms, including the coordina-tio…
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