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Jul 29, 2017
From ICCV
Computer Vision

Visual Relationship Detection with Internal and External Linguistic...

Understanding visual relationships involves identifying the subject, the object, and a predicate relating them. We leverage the strong correlations...
Dec 22, 2014
From NIPS
Computation and Language
Machine Learning

Bayesian Optimisation for Machine Translation

This paper presents novel Bayesian optimisation algorithms for minimum error rate training of statistical machine translation systems. We explore t...
Jan 24, 2017
By rmitter
From ICCV
Computer Vision

Improved Descriptors for Patch Matching and Reconstruction

We propose a convolutional neural network (ConvNet) based approach for learning local image descriptors which can be used for significantly improve...
May 18, 2017
From ICLR
Machine Learning

Delving into adversarial attacks on deep policies

Adversarial examples have been shown to exist for a variety of deep learning architectures. Deep reinforcement learning has shown promising results...
May 21, 2016
From ICML
Neural and Evolutionary Computation
Artificial Intelligence
Machine Learning

Programming with a Differentiable Forth Interpreter

Given that in practice training data is scarce for all but a small set of problems, a core question is how to incorporate prior knowledge into a mo...
Aug 09, 2017
From CVPR
Computer Vision
Computation and Language

Tips and Tricks for Visual Question Answering: Learnings from the 2...

This paper presents a state-of-the-art model for visual question answering (VQA), which won the first place in the 2017 VQA Challenge. VQA is a tas...
Mar 30, 2018
From CVPR
Computer Vision

Transductive Unbiased Embedding for Zero-Shot Learning

Most existing Zero-Shot Learning (ZSL) methods have the strong bias problem, in which instances of unseen (target) classes tend to be categorized a...
Nov 18, 2017
From NIPS
Machine Learning
Applications

Household poverty classification in data-scarce environments: a mac...

We describe a method to identify poor households in data-scarce countries by leveraging information contained in nationally representative househol...
Apr 21, 2016
By lyndonk
From ECCV
Computer Vision
Information Retrieval
Multimedia

LOH and behold: Web-scale visual search, recommendation and cluster...

We propose a novel hashing-based matching scheme, called Locally Optimized Hashing (LOH), based on a state-of-the-art quantization algorithm that c...
Mar 27, 2018
From CVPR
Computer Vision
Computation and Language

Neural Baby Talk

We introduce a novel framework for image captioning that can produce natural language explicitly grounded in entities that object detectors find in...
Feb 14, 2017
From ICLR
Machine Learning
Artificial Intelligence
Computer Vision

On Detecting Adversarial Perturbations

Machine learning and deep learning in particular has advanced tremendously on perceptual tasks in recent years. However, it remains vulnerable agai...
Sep 01, 2016
From ECCV
Computer Vision
Artificial Intelligence
Machine Learning

Human Pose Estimation in Space and Time using 3D CNN

This paper explores the capabilities of convolutional neural networks to deal with a task that is easily manageable for humans: perceiving 3D pose ...
Jun 13, 2017
From ICLR
Machine Learning
Artificial Intelligence
Information Retrieval
Neural and Evolutionary Computation

Getting deep recommenders fit: Bloom embeddings for sparse binary ...

Recommendation algorithms that incorporate techniques from deep learning are becoming increasingly popular. Due to the structure of the data coming...
Apr 07, 2016
From CVPR
Computer Vision

Joint Detection and Identification Feature Learning for Person Search

Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates. However...
Sep 11, 2017
From ICRA
Artificial Intelligence
Robotics

Autonomous Quadrotor Landing using Deep Reinforcement Learning

Landing an unmanned aerial vehicle (UAV) on a ground marker is an open problem despite the effort of the research community. Previous attempts most...
Mar 30, 2018
From CVPR
Computer Vision

Learning Structure and Strength of CNN Filters for Small Sample Siz...

Convolutional Neural Networks have provided state-of-the-art results in several computer vision problems. However, due to a large number of paramet...
Jun 08, 2015
By etg
From NIPS
Neural and Evolutionary Computation
Computation and Language
Machine Learning

Learning to Transduce with Unbounded Memory

Recently, strong results have been demonstrated by Deep Recurrent Neural Networks on natural language transduction problems. In this paper we explo...
Jun 18, 2016
From ICML
Machine Learning

As a contribution to interpretable machine learning research, we develop a novel optimization framework for learning accurate and sparse two-level Boolean rules. We consider rules in both conjunctive normal form (AND-of-ORs) and disjunctive normal...

Interpretable Two-level Boolean Rule Learning for Classification

As a contribution to interpretable machine learning research, we develop a novel optimization framework for learning accurate and sparse two-level ...
May 18, 2017
From MICCAI
Computer Vision

Model-based Catheter Segmentation in MRI-images

Accurate and reliable segmentation of catheters in MR-gui- ded interventions remains a challenge, and a step of critical importance in clinical wor...
Jul 12, 2017
From ICML
Artificial Intelligence

A Formal Framework to Characterize Interpretability of Procedures

We provide a novel notion of what it means to be interpretable, looking past the usual association with human understanding. Our key insight is tha...
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