Amazon

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Amazon.co.uk, Inc., is an American multinational technology company based in Seattle, Washington that focuses on e-commerce, cloud computing, digital streaming and artificial intelligence.

P3O: Policy-on Policy-off Policy Optimization

On-policy reinforcement learning (RL) algorithms have high sample comple...
05/05/2019 ∙ by Rasool Fakoor, et al. ∙ 36 ∙ share

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Continual Universal Object Detection

Object detection has improved significantly in recent years on multiple ...
02/13/2020 ∙ by Xialei Liu, et al. ∙ 33 ∙ share

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Action recognition with spatial-temporal discriminative filter banks

Action recognition has seen a dramatic performance improvement in the la...
08/20/2019 ∙ by Brais Martinez, et al. ∙ 26 ∙ share

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SAVEHR: Self Attention Vector Representations for EHR based Personalized Chronic Disease Onset Prediction and Interpretability

Chronic disease progression is emerging as an important area of investme...
11/13/2019 ∙ by Sunil Mallya, et al. ∙ 26 ∙ share

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OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations

We present a novel model called OCGAN for the classical problem of one-c...
03/20/2019 ∙ by Pramuditha Perera, et al. ∙ 22 ∙ share

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Region Proposal by Guided Anchoring

Region anchors are the cornerstone of modern object detection techniques...
01/10/2019 ∙ by Jiaqi Wang, et al. ∙ 20 ∙ share

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Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Neural Networks

We explore the problem of selectively forgetting a particular set of dat...
11/12/2019 ∙ by Aditya Golatkar, et al. ∙ 20 ∙ share

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Scale-Aware Attention Network for Crowd Counting

In crowd counting datasets, people appear at different scales, depending...
01/17/2019 ∙ by Rahul Rama Varior, et al. ∙ 17 ∙ share

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Incremental Learning for Metric-Based Meta-Learners

Majority of the modern meta-learning methods for few-shot classification...
02/11/2020 ∙ by Qing Liu, et al. ∙ 17 ∙ share

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Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications

Trained on large datasets, deep learning (DL) can accurately classify vi...
03/03/2020 ∙ by Biagio Brattoli, et al. ∙ 17 ∙ share

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Scalable Logo Recognition using Proxies

Logo recognition is the task of identifying and classifying logos. Logo ...
11/19/2018 ∙ by Istvan Fehervari, et al. ∙ 16 ∙ share

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Language Models with Transformers

The Transformer architecture is superior to RNN-based models in computat...
04/20/2019 ∙ by Chenguang Wang, et al. ∙ 16 ∙ share

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A Human-AI Loop Approach for Joint Keyword Discovery and Expectation Estimation in Micropost Event Detection

Microblogging platforms such as Twitter are increasingly being used in e...
12/02/2019 ∙ by Akansha Bhardwaj, et al. ∙ 16 ∙ share

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From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap

Dialogue state tracking (DST) is at the heart of task-oriented dialogue ...
04/13/2020 ∙ by Shuyang Gao, et al. ∙ 16 ∙ share

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Towards classification parity across cohorts

Recently, there has been a lot of interest in ensuring algorithmic fairn...
05/16/2020 ∙ by Aarsh Patel, et al. ∙ 16 ∙ share

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TextTubes for Detecting Curved Text in the Wild

We present a detector for curved text in natural images. We model scene ...
12/19/2019 ∙ by Joël Seytre, et al. ∙ 15 ∙ share

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MT-BioNER: Multi-task Learning for Biomedical Named Entity Recognition using Deep Bidirectional Transformers

Conversational agents such as Cortana, Alexa and Siri are continuously w...
01/24/2020 ∙ by Muhammad Raza Khan, et al. ∙ 15 ∙ share

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Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation

Direct prediction of 3D body pose and shape remains a challenge even for...
08/17/2018 ∙ by Mohamed Omran, et al. ∙ 14 ∙ share

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Differentially Private Consensus-Based Distributed Optimization

Data privacy is an important concern in learning, when datasets contain ...
03/19/2019 ∙ by Mehrdad Showkatbakhsh, et al. ∙ 14 ∙ share

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FACSIMILE: Fast and Accurate Scans From an Image in Less Than a Second

Current methods for body shape estimation either lack detail or require ...
09/02/2019 ∙ by David Smith, et al. ∙ 14 ∙ share

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SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction

Open relation extraction is the task of extracting open-domain relation ...
04/06/2020 ∙ by Xuming Hu, et al. ∙ 14 ∙ share

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Recognizing Variables from their Data via Deep Embeddings of Distributions

A key obstacle in automated analytics and meta-learning is the inability...
09/11/2019 ∙ by Jonas Mueller, et al. ∙ 13 ∙ share

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Imitation-Regularized Offline Learning

We study the problem of offline learning in automated decision systems u...
01/15/2019 ∙ by Yifei Ma, et al. ∙ 12 ∙ share

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Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources

With an increasing demand for training powers for deep learning algorith...
04/26/2019 ∙ by Haibin Lin, et al. ∙ 12 ∙ share

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A Linear Bandit for Seasonal Environments

Contextual bandit algorithms are extremely popular and widely used in re...
04/28/2020 ∙ by Giuseppe Di Benedetto, et al. ∙ 12 ∙ share

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Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering

BERT model has been successfully applied to open-domain QA tasks. Howeve...
08/22/2019 ∙ by Zhiguo Wang, et al. ∙ 11 ∙ share

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Weakly Supervised Energy-Based Learning for Action Segmentation

This paper is about labeling video frames with action classes under weak...
09/28/2019 ∙ by Jun Li, et al. ∙ 11 ∙ share

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Large Scale Open-Set Deep Logo Detection

We present an open-set logo detection (OSLD) system, which can detect (l...
11/18/2019 ∙ by Muhammet Bastan, et al. ∙ 11 ∙ share

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Words aren't enough, their order matters: On the Robustness of Grounding Visual Referring Expressions

Visual referring expression recognition is a challenging task that requi...
05/04/2020 ∙ by Arjun R Akula, et al. ∙ 11 ∙ share

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Coupled Recurrent Models for Polyphonic Music Composition

This work describes a novel recurrent model for music composition, which...
11/20/2018 ∙ by John Thickstun, et al. ∙ 10 ∙ share

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Task2Vec: Task Embedding for Meta-Learning

We introduce a method to provide vectorial representations of visual cla...
02/10/2019 ∙ by Alessandro Achille, et al. ∙ 10 ∙ share

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Communication-efficient distributed SGD with Sketching

Large-scale distributed training of neural networks is often limited by ...
03/12/2019 ∙ by Nikita Ivkin, et al. ∙ 10 ∙ share

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HyperStream: a Workflow Engine for Streaming Data

This paper describes HyperStream, a large-scale, flexible and robust sof...
08/07/2019 ∙ by Tom Diethe, et al. ∙ 9 ∙ share

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A Baseline for Few-Shot Image Classification

Fine-tuning a deep network trained with the standard cross-entropy loss ...
09/06/2019 ∙ by Guneet S. Dhillon, et al. ∙ 9 ∙ share

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Acoustic scene analysis with multi-head attention networks

Acoustic Scene Classification (ASC) is a challenging task, as a single s...
09/16/2019 ∙ by Weimin Wang, et al. ∙ 9 ∙ share

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Toward Understanding Catastrophic Forgetting in Continual Learning

We study the relationship between catastrophic forgetting and properties...
08/02/2019 ∙ by Cuong V. Nguyen, et al. ∙ 8 ∙ share

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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking

Counterfactual thinking describes a psychological phenomenon that people...
08/13/2019 ∙ by Yue Wang, et al. ∙ 7 ∙ share

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Robustness to Capitalization Errors in Named Entity Recognition

Robustness to capitalization errors is a highly desirable characteristic...
11/13/2019 ∙ by Sravan Bodapati, et al. ∙ 7 ∙ share

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The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution

While implicit generative models such as GANs have shown impressive resu...
07/31/2018 ∙ by Muhammad Waleed Gondal, et al. ∙ 6 ∙ share

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Improving noise robustness of automatic speech recognition via parallel data and teacher-student learning

For real-world speech recognition applications, noise robustness is stil...
01/05/2019 ∙ by Ladislav Mošner, et al. ∙ 6 ∙ share

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Variational Information Distillation for Knowledge Transfer

Transferring knowledge from a teacher neural network pretrained on the s...
04/11/2019 ∙ by Sungsoo Ahn, et al. ∙ 6 ∙ share

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Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training

We propose a method for learning embeddings for few-shot learning that i...
05/10/2019 ∙ by Avinash Ravichandran, et al. ∙ 6 ∙ share

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Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

How can we estimate the importance of nodes in a knowledge graph (KG)? A...
05/21/2019 ∙ by Namyong Park, et al. ∙ 6 ∙ share

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Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System

In real-world question-answering (QA) systems, ill-formed questions, suc...
08/13/2019 ∙ by Ye Liu, et al. ∙ 6 ∙ share

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TracKlinic: Diagnosis of Challenge Factors in Visual Tracking

Generic visual tracking is difficult due to many challenge factors (e.g....
11/18/2019 ∙ by Heng Fan, et al. ∙ 6 ∙ share

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The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models

Time series modeling techniques based on deep learning have seen many ad...
05/20/2020 ∙ by Stephan Rabanser, et al. ∙ 6 ∙ share

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GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing

We present GluonCV and GluonNLP, the deep learning toolkits for computer...
07/09/2019 ∙ by Jian Guo, et al. ∙ 5 ∙ share

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Deep Perceptual Compression

Several deep learned lossy compression techniques have been proposed in ...
07/18/2019 ∙ by Yash Patel, et al. ∙ 5 ∙ share

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Controllable Variational Autoencoder

Variational Autoencoders (VAE) and their variants have been widely used ...
04/13/2020 ∙ by Huajie Shao, et al. ∙ 5 ∙ share

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Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

We propose a meta-learning approach that learns from multiple tasks in a...
04/27/2020 ∙ by Shell Xu Hu, et al. ∙ 5 ∙ share

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