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Feb 24, 2020
Machine Learning
Computer Vision

Deep Nearest Neighbor Anomaly Detection

Nearest neighbors is a successful and long-standing technique for anomaly detection. Significant progress has been recently achieved by self-supervis…
Feb 24, 2020
Machine Learning
Computer Vision

Batch Normalization Biases Deep Residual Networks Towards Shallow Pat…

Batch normalization has multiple benefits. It improves the conditioning of the loss landscape, and is a surprisingly effective regularizer. However, …
Feb 24, 2020
Machine Learning

LogicGAN: Logic-guided Generative Adversarial Networks

Generative Adversarial Networks (GANs) are a revolutionary class of Deep Neural Networks (DNNs) that have been successfully used to generate realisti…
Feb 24, 2020
Computer Vision

Maximum Entropy on the Mean: A Paradigm Shift for Regularization in …

Image deblurring is a notoriously challenging ill-posed inverse problem. In recent years, a wide variety of approaches have been proposed based upon …
Feb 24, 2020
Artificial Intelligence
Machine Learning

From Chess and Atari to StarCraft and Beyond: How Game AI is Driving …

This paper reviews the field of Game AI, which not only deals with creating agents that can play a certain game, but also with areas as diverse as cr…
Feb 24, 2020
Machine Learning

Neural Message Passing on High Order Paths

Graph neural network have achieved impressive results in predicting molecular properties, but they do not directly account for local and hidden struc…
Feb 24, 2020
Machine Learning

Lagrangian Decomposition for Neural Network Verification

A fundamental component of neural network verification is the computation of bounds on the values their outputs can take. Previous methods have eithe…
Feb 24, 2020
Machine Learning

Closing the convergence gap of SGD without replacement

Stochastic gradient descent without replacement sampling is widely used in practice for model training. However, the vast majority of SGD analyses as…
Feb 24, 2020
Methodology
Machine Learning

Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference…

Parameter estimation, statistical tests and confidence sets are the cornerstones of classical statistics that allow scientists to make inferences abo…
Feb 24, 2020
Computer Vision

Suppressing Uncertainties for Large-Scale Facial Expression Recogniti…

Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions…
Feb 24, 2020
Machine Learning

Semi-Supervised Neural Architecture Search

Neural architecture search (NAS) relies on a good controller to generate better architectures or predict the accuracy of given architectures. However…
Feb 24, 2020
Computational Finance
Machine Learning

Predictive intraday correlations in stable and volatile market envi…

Standard methods and theories in finance can be ill-equipped to capture highly non-linear interactions in financial prediction problems based on larg…
Feb 24, 2020
Computer Vision

Sketchformer: Transformer-based Representation for Sketched Structure

Sketchformer is a novel transformer-based representation for encoding free-hand sketches input in a vector form, i.e. as a sequence of strokes. Sketc…
Feb 24, 2020
Machine Learning
Neurons and Cognition

Supervised Deep Similarity Matching

We propose a novel biologically-plausible solution to the credit assignment problem, being motivated by observations in the ventral visual pathway an…
Feb 24, 2020
Machine Learning

The Two Regimes of Deep Network Training

Learning rate schedule has a major impact on the performance of deep learning models. Still, the choice of a schedule is often heuristical. We aim to…
Feb 24, 2020
Computation and Language
Machine Learning

Discriminative Adversarial Search for Abstractive Summarization

We introduce a novel approach for sequence decoding, Discriminative Adversarial Search (DAS), which has the desirable properties of alleviating the e…
Feb 24, 2020
Artificial Intelligence

Symbolic Learning and Reasoning with Noisy Data for Probabilistic A…

Robotic agents should be able to learn from sub-symbolic sensor data, and at the same time, be able to reason about objects and communicate with huma…
Feb 24, 2020
Machine Learning
Neural and Evolutionary Computation

The Early Phase of Neural Network Training

Recent studies have shown that many important aspects of neural network learning take place within the very earliest iterations or epochs of training…
Feb 24, 2020
Computer Vision
Cryptography and Security

Joint Learning of Assignment and Representation for Biometric Group …

This paper proposes a framework for group membership protocols preventing the curious but honest server from reconstructing the enrolled biometric si…
Feb 24, 2020
Cryptography and Security
Computer Vision

Group Membership Verification with Privacy: Sparse or Dense?

Group membership verification checks if a biometric trait corresponds to one member of a group without revealing the identity of that member. Recent …
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