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Nov 15, 2019
Machine Learning
Data Structures and Algorithms

Non-Monotone Submodular Maximization with Multiple Knapsacks in Stati…

We study the problem of maximizing a non-monotone submodular function under multiple knapsack constraints. We propose a simple discrete greedy algori…
Nov 15, 2019
Machine Learning
Computer Vision

Stagewise Knowledge Distillation

The deployment of modern Deep Learning models requires high computational power. However, many applications are targeted for embedded devices like sm…
Nov 15, 2019
Disordered Systems and Neural Networks
Machine Learning

Clustering of solutions in the symmetric binary perceptron

The geometrical features of the (non-convex) loss landscape of neural network models are crucial in ensuring successful optimization and, most import…
Nov 15, 2019
Machine Learning

Unsupervised Attributed Multiplex Network Embedding

Nodes in a multiplex network are connected by multiple types of relations. However, most existing network embedding methods assume that only a single…
Nov 15, 2019
Computation and Language
Artificial Intelligence
Human-Computer Interaction
Machine Learning

Towards Personalized Dialog Policies for Conversational Skill Discove…

Many businesses and consumers are extending the capabilities of voice-based services such as Amazon Alexa, Google Home, Microsoft Cortana, and Apple …
Nov 15, 2019
Machine Learning

Penalized k-means algorithms for finding the correct number of cluste…

In many applications we want to find the number of clusters in a dataset. A common approach is to use the penalized k-means algorithm with an additiv…
Nov 15, 2019
Methodology
Computers and Society
Statistics Theory
Data Analysis
Statistics and Probability
Machine Learning

A nonparametric framework for inferring orders of categorical data fr…

Given a dataset of careers and incomes, how large a difference of income between any pair of careers would be? Given a dataset of travel time records…
Nov 15, 2019
Methodology
Machine Learning

Causal inference using Bayesian non-parametric quasi-experimental des…

The de facto standard for causal inference is the randomized controlled trial, where one compares an manipulated group with a control group in order …
Nov 15, 2019
Computer Vision

In-domain representation learning for remote sensing

Given the importance of remote sensing, surprisingly little attention has been paid to it by the representation learning community. To address it and…
Nov 15, 2019
Machine Learning

A Generalized Markov Chain Model to Capture Dynamic Preferences and …

Assortment optimization is an important problem that arises in many practical applications such as retailing and online advertising where the goal is…
Nov 15, 2019
Machine Learning
Artificial Intelligence

Fair Data Adaptation with Quantile Preservation

Fairness of classification and regression has received much attention recently and various, partially non-compatible, criteria have been proposed. Th…
Nov 15, 2019
Machine Learning

Generative Models for Effective ML on Private, Decentralized Datasets

To improve real-world applications of machine learning, experienced modelers develop intuition about their datasets, their models, and how the two in…
Nov 15, 2019
Computation and Language

Bootstrapping NLU Models with Multi-task Learning

Bootstrapping natural language understanding (NLU) systems with minimal training data is a fundamental challenge of extending digital assistants like…
Nov 15, 2019
Computational Physics
Machine Learning

Enforcing Deterministic Constraints on Generative Adversarial Network…

Generative adversarial networks (GANs) are initially proposed to generate images by learning from a large number of samples. Recently, GANs have been…
Nov 15, 2019
Computer Vision

CenterMask : Real-Time Anchor-Free Instance Segmentation

We propose a simple yet efficient anchor-free instance segmentation, called CenterMask, that adds a novel spatial attention-guided mask (SAG-Mask) br…
Nov 15, 2019
Machine Learning
Computer Vision

MMGAN: Generative Adversarial Networks for Multi-Modal Distributions

Over the past years, Generative Adversarial Networks (GANs) have shown a remarkable generation performance especially in image synthesis. Unfortunate…
Nov 15, 2019
Artificial Intelligence

A Policy Editor for Semantic Sensor Networks

An important use of sensors and actuator networks is to comply with health and safety policies in hazardous environments. In order to deal with incre…
Nov 15, 2019
Machine Learning

Imputing missing values with unsupervised random trees

This work proposes a non-iterative strategy for missing value imputations which is guided by similarity between observations, but instead of explicit…
Nov 15, 2019
Computer Vision

You Only Watch Once: A Unified CNN Architecture for Real-Time Spati…

Spatiotemporal action localization requires incorporation of two sources of information into the designed architecture: (1) Temporal information from…
Nov 15, 2019
Computation and Language
Machine Learning
Neural and Evolutionary Computation

CatGAN: Category-aware Generative Adversarial Networks with Hierarchi…

Generating multiple categories of texts is a challenging task and draws more and more attention. Since generative adversarial nets (GANs) have shown …
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