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May 23, 2019
By pabbeel
Machine Learning

MCP: Learning Composable Hierarchical Control with Multiplicative ...

Humans are able to perform a myriad of sophisticated tasks by drawing upon skills acquired through prior experience. For autonomous agents to have ...
May 23, 2019
By bmoews
Computation
Methodology

Gaussbock: Fast parallel-iterative cosmological parameter estimatio...

We present and apply Gaussbock, a new embarrassingly parallel iterative algorithm for cosmological parameter estimation designed for an era of chea...
May 23, 2019
Machine Learning
Computer Vision

Interpreting Adversarially Trained Convolutional Neural Networks

We attempt to interpret how adversarially trained convolutional neural networks (AT-CNNs) recognize objects. We design systematic approaches to int...
May 23, 2019
Machine Learning
Artificial Intelligence

Augmenting correlation structures in spatial data using deep genera...

State-of-the-art deep learning methods have shown a remarkable capacity to model complex data domains, but struggle with geospatial data. In this p...
May 23, 2019
Machine Learning

Multi-relational Poincaré Graph Embeddings

Hyperbolic embeddings have recently gained attention in machine learning due to their ability to represent hierarchical data more accurately and su...
May 23, 2019
By joe

Verification of independent quantum devices

Quantum computers are on the brink of surpassing the capabilities of even the most powerful classical computers. This naturally raises the question...
May 23, 2019
Neural and Evolutionary Computation
Computer Vision

Multi-Sample Dropout for Accelerated Training and Better Generaliza...

Dropout is a simple but efficient regularization technique for achieving better generalization of deep neural networks (DNNs); hence it is widely u...
May 23, 2019
By jtkim
Machine Learning

Bayesian Optimization over Sets

We propose a Bayesian optimization method over sets, to minimize a black-box function that can take a set as single input. Because set inputs are p...
May 23, 2019
By pvh
Cryptography and Security
Artificial Intelligence

Privacy-Preserving Obfuscation of Critical Infrastructure Networks

The paper studies how to release data about a critical infrastructure network (e.g., the power network or a transportation network) without disclos...
May 23, 2019
By charly

Can fermionic dark matter mimic supermassive black holes?

We analyze the intriguing possibility to explain both dark mass components in a galaxy: the dark matter (DM) halo and the supermassive dark compact...
May 23, 2019
By taehyun
Computer Vision
Multimedia

Speech2Face: Learning the Face Behind a Voice

How much can we infer about a person's looks from the way they speak? In this paper, we study the task of reconstructing a facial image of a person...
May 23, 2019
Machine Learning
Networking and Internet Architecture
Signal Processing

Multi-Service Mobile Traffic Forecasting via Convolutional Long S...

Network slicing is increasingly used to partition network infrastructure between different mobile services. Precise service-wise mobile traffic for...
May 23, 2019
Machine Learning

Zero-shot Knowledge Transfer via Adversarial Belief Matching

Performing knowledge transfer from a large teacher network to a smaller student is a popular task in modern deep learning applications. However, du...
May 23, 2019
By leo
Machine Learning
Information Retrieval

Geometric Laplacian Eigenmap Embedding

Graph embedding seeks to build a low-dimensional representation of a graph G. This low-dimensional representation is then used for various downstre...
May 23, 2019
By mchowdh
Data Structures and Algorithms
Computation and Language
Information Retrieval

An Efficient Approach for Super and Nested Term Indexing and Retrieval

This paper describes a new approach, called Terminological Bucket Indexing (TBI), for efficient indexing and retrieval of both nested and super ter...
May 23, 2019
By edizel
Computation and Language
Machine Learning

Misspelling Oblivious Word Embeddings

In this paper we present a method to learn word embeddings that are resilient to misspellings. Existing word embeddings have limited applicability ...
May 23, 2019
By xinkun
Methodology
Machine Learning

Learning When-to-Treat Policies

Many applied decision-making problems have a dynamic component: The policymaker needs not only to choose whom to treat, but also when to start whic...
May 23, 2019
Machine Learning
Computer Vision

Adversarially Robust Distillation

Knowledge distillation is effective for producing small high-performance neural networks for classification, but these small networks are vulnerabl...
May 23, 2019
Data Analysis
Statistics and Probability
Machine Learning
Computational Physics
Fluid Dynamics

A Predictive Model for Steady-State Multiphase Pipe Flow: Machine ...

Engineering simulators used for steady-state multiphase pipe flows are commonly utilized to predict pressure drop. Such simulators are typically ba...
May 23, 2019
By azencot
Numerical Analysis

Consistent Dynamic Mode Decomposition

We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the ma...
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