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Oct 18, 2018
Computer Vision
Artificial Intelligence
Information Retrieval
Machine Learning

Convolutional Collaborative Filter Network for Video Based Recomm...

This analysis explores the temporal sequencing of objects in a movie trailer. Temporal sequencing of objects in a movie trailer (e.g., a long shot ...
Oct 18, 2018
Machine Learning
Artificial Intelligence

Gradient Agreement as an Optimization Objective for Meta-Learning

This paper presents a novel optimization method for maximizing generalization over tasks in meta-learning. The goal of meta-learning is to learn a ...
Oct 18, 2018
Robotics

Establishing Appropriate Trust via Critical States

In order to effectively interact with or supervise a robot, humans need to have an accurate mental model of its capabilities and how it acts. Learn...
Oct 18, 2018
By ninamf
Data Structures and Algorithms
Machine Learning

Testing Matrix Rank, Optimally

We show that for the problem of testing if a matrix $A \in F^{n \times n}$ has rank at most $d$, or requires changing an $\epsilon$-fraction of ent...
Oct 18, 2018
Image and Video Processing
Computer Vision
Multimedia

Exploiting High-Level Semantics for No-Reference Image Quality As...

To guarantee a satisfying Quality of Experience (QoE) for consumers, it is required to measure image quality efficiently and reliably. The neglect ...
Oct 18, 2018
By mk898
Robotics

Expressing Robot Incapability

Our goal is to enable robots to express their incapability, and to do so in a way that communicates both what they are trying to accomplish and why...
Oct 18, 2018
Machine Learning

Exploiting Correlation in Finite-Armed Structured Bandits

We consider a correlated multi-armed bandit problem in which rewards of arms are correlated through a hidden parameter. Our approach exploits the c...
Oct 18, 2018
Machine Learning
Artificial Intelligence

Fast deep reinforcement learning using online adjustments from the ...

We propose Ephemeral Value Adjusments (EVA): a means of allowing deep reinforcement learning agents to rapidly adapt to experience in their replay ...
Oct 18, 2018
Artificial Intelligence

Planning in Stochastic Environments with Goal Uncertainty

We present the Goal Uncertain Stochastic Shortest Path (GUSSP) problem --- a general framework to model stochastic environments with goal uncertain...
Oct 18, 2018
By robw
Robotics

Probably Unknown: Deep Inverse Sensor Modelling In Radar

Radar presents a promising alternative to lidar and vision in autonomous vehicle applications, being able to detect objects at long range under a v...
Oct 18, 2018
By ckhatri
Computation and Language

Contextual Topic Modeling For Dialog Systems

Accurate prediction of conversation topics can be a valuable signal for creating coherent and engaging dialog systems. In this work, we focus on co...
Oct 18, 2018
Cryptography and Security
Machine Learning

We have proposed an open source framework for experimenting with secure computation in TensorFlow, and illustrated how implementation of such protocols can be easily expressed using high level abstractions (Figure 2). This additionally allows priv...

Private Machine Learning in TensorFlow using Secure Computation

We present a framework for experimenting with secure multi-party computation directly in TensorFlow. By doing so we benefit from several properties...
Oct 18, 2018
By ms4415
Machine Learning
Computer Vision

KTAN: Knowledge Transfer Adversarial Network

To reduce the large computation and storage cost of a deep convolutional neural network, the knowledge distillation based methods have pioneered to...
Oct 18, 2018
Robotics
Cryptography and Security

Procedurally Provisioned Access Control for Robotic Systems

Security of robotics systems, as well as of the related middleware infrastructures, is a critical issue for industrial and domestic IoT, and it nee...
Oct 18, 2018
By lalkanj
Artificial Intelligence

Approximate Dynamic Programming for Planning a Ride-Sharing System ...

Within a decade, almost every major auto company, along with fleet operators such as Uber, have announced plans to put autonomous vehicles on the r...
Oct 18, 2018
Computer Vision

Salience Biased Loss for Object Detection in Aerial Images

Object detection in remote sensing, especially in aerial images, remains a challenging problem due to low image resolution, complex backgrounds, an...
Oct 18, 2018
Machine Learning

First-order and second-order variants of the gradient descent: a un...

In this paper, we provide an overview of first-order and second-order variants of the gradient descent methods commonly used in machine learning. W...
Oct 18, 2018
By wlj
Computer Vision

DeepLens: Shallow Depth Of Field From A Single Image

We aim to generate high resolution shallow depth-of-field (DoF) images from a single all-in-focus image with controllable focal distance and apertu...
Oct 18, 2018
Computer Vision

Stochastic Distance Transform

The distance transform (DT) and its many variations are ubiquitous tools for image processing and analysis. In many imaging scenarios, the images o...
Oct 18, 2018
By rossi
Machine Learning

Good Initializations of Variational Bayes for Deep Models

Stochastic variational inference is an established way to carry out approximate Bayesian inference for deep models. While there have been effective...
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