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Taskonomy | Stanford

<b>Transfer Function.</b> We use one or multiple source tasks to predict a target task's output.<p>Task Bank: A Unified Bank of 25 Pretrained Visual Estimators

The Annotated Transformer

The Transformer from “Attention is All You Need” has been on a lot of people’s minds over the last year. Besides producing major improvements in …

Deep Learning

NVIDIA at CVPR 2018

NVIDIA AT CVPR 2018<p>At the forefront of AI innovations, NVIDIA continues to push the boundaries of technology in machine learning, computer vision, …

Deep Learning

Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories. (arXiv:1806.05357v1 [cs.LG])

Authors: Ian Fox, Lynn Ang, Mamta Jaiswal, Rodica Pop-Busui, Jenna WiensIn many forecasting applications, it is valuable to predict not only the …

Machine Learning

How will the GDPR impact machine learning?

<i>Answers to the three most commonly asked questions about maintaining GDPR-compliant machine learning programs.</i>Much has been made about the potential …

Machine Learning

Apple ha riconosciuto e confermato un problema che riguarda gli ultimi modelli di <b>MacBook Pro da 13″</b>. In particolare si tratta di <b>malfunzionamenti</b> …

Researchers have released the largest self-driving-car data set yet

The BDD100K data set, made up of 100,000 videos recorded onboard autonomous cars, is now available for download from the University of California, …

University of California

AI can transfer human facial movements from one video to another

Researchers have taken another step towards realistic, synthesized video. The team, made up of scientists in Germany, France, the UK and the US, used AI to transfer the head poses, facial expressions, eye motions and blinks of a person in one video onto another entirely different person in a …

Robotics

Do Better ImageNet Models Transfer Better?. (arXiv:1805.08974v1 [cs.CV])

Authors: Simon Kornblith, Jonathon Shlens, Quoc V. LeTransfer learning has become a cornerstone of computer vision with the advent of ImageNet …

Machine Learning

Yann LeCun

How researchers are teaching AI to learn like a child

YouTube

Gym Retro

We're releasing the full version of Gym Retro, a platform for reinforcement learning research on games. This brings our publicly-released game count …

Machine Learning

Been There, Done That: Meta-Learning with Episodic Recall. (arXiv:1805.09692v1 [stat.ML])

Authors: Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell, Razvan Pascanu, Matthew BotvinickMeta-learning …

arXiv

AI Researchers Are Boycotting Nature’s New Machine Intelligence Journal

Researchers from Google, Facebook, IBM, MIT and Harvard have pledged not to contribute to a new journal about machine learning, citing its lack of open access.<p>Springer Nature, the publisher of <i>Scientific American</i> and the venerable scientific journal <i>Nature</i>, intends to stride into the white-hot field …

An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identification. (arXiv:1805.06086v1 [cs.CV])

In recent years, a variety of proposed methods based on deep convolutional neural networks (CNNs) have improved the state of the art for large-scale …

Progress & Compress: A scalable framework for continual learning. (arXiv:1805.06370v1 [stat.ML])

Authors: Jonathan Schwarz, Jelena Luketina, Wojciech M. Czarnecki, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia HadsellWe …

Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation. (arXiv:1805.04574v2 [cs.CV] UPDATED)

Despite the remarkable progress, weakly supervised segmentation approaches are still inferior to their fully supervised counterparts. We obverse the …

Constrained-CNN losses forweakly supervised segmentation. (arXiv:1805.04628v1 [cs.CV])

Weak supervision, e.g., in the form of partial labels or image tags, is currently attracting significant attention in CNN segmentation as it can …

Born Again Neural Networks. (arXiv:1805.04770v1 [stat.ML])

Authors: Tommaso Furlanello, Zachary C. Lipton, Michael Tschannen, Laurent Itti, Anima AnandkumarKnowledge distillation (KD) consists of transferring …

[R] Introducing state of the art text classification with universal language models

submitted by /u/desku to r/MachineLearning <br>[link] [comments]

From Word to Sense Embeddings: A Survey on Vector Representations of Meaning. (arXiv:1805.04032v2 [cs.CL] UPDATED)

Authors: Jose Camacho-Collados, Mohammad Taher PilehvarOver the past years, distributed representations have proven effective and flexible keepers of …

Quick test of tensorflow.js and posenet. (Inspired by Matisse, using Macbook Pro, visualized with pts.js) 😀 #Tensorflowjs #ptsjs https://t.co/TqJp3cy8Sl

Attention-Aware Compositional Network for Person Re-identification. (arXiv:1805.03344v2 [cs.CV] UPDATED)

Person re-identification (ReID) is to identify pedestrians observed from different camera views based on visual appearance. It is a challenging task …

Boosting Domain Adaptation by Discovering Latent Domains. (arXiv:1805.01386v1 [cs.CV])

Current Domain Adaptation (DA) methods based on deep architectures assume that the source samples arise from a single distribution. However, in …

Siamese networks for generating adversarial examples. (arXiv:1805.01431v1 [cs.LG])

Authors: Mandar Kulkarni, Aria AbubakarMachine learning models are vulnerable to adversarial examples. An adversary modifies the input data such that …

Variational Autoencoders

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Evaluation of CNN-based Single-Image Depth Estimation Methods. (arXiv:1805.01328v1 [cs.CV])

While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are …

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

This is an official python implementation of PRN. The training code will be released(about two months later).<p>PRN is a method to jointly regress dense …