DeepMind & Google Explore Hyperparameter Selection for Offline RL
Researchers conducted a thorough empirical study of hyperparameter selection for offline RL, aiming to identify and develop more reliable and effective approaches.
Category: Machine Learning & Data Science
Unselfie Turns Arm-Extended Selfies into Neutral-Pose Portraits
“Unselfie,” a novel photographic transformation model that can automatically translate selfies into neutral-pose portraits.
AI Generator Learns to ‘Draw’ Like Cartoonist Lee Mal-Nyeon in Just 10 Hours
A Seoul National University Master’s student and developer has trained a face generating model to transfer normal face photographs into cartoon images in the distinctive style of Lee Mal-nyeon.
As Its GPT-3 Model Wows the World, OpenAI CEO Suggests ‘the Hype Is Way Too Much’
OpenAI’s 175 billion parameter language model GPT-3 has gone viral once again.
Google ‘BigBird’ Achieves SOTA Performance on Long-Context NLP Tasks
BigBird is shown to dramatically improve performance across long-context NLP tasks, producing SOTA results in question answering and summarization.
Applying Linearly Scalable Transformers to Model Longer Protein Sequences
Researchers proposed a new transformer architecture called “Performer” — based on what they call fast attention via orthogonal random features (FAVOR).
AI-Powered ‘Genderify’ Platform Shut Down After Bias-Based Backlash
Genderify is an AI-powered tool designed to identify a person’s gender by analyzing their name, username or email address.
Preferred Networks Releases PFRL Deep Reinforcement Learning Library for PyTorch Users
PFRL succeeds ChainerRL as comprehensive library with cutting-edge deep reinforcement learning algorithms and features.
MLPerf Training v0.7 Results Released: Google & NVIDIA Lead the Race
The industry-standard MLPerf benchmark today released the results of the third round of its ongoing ML Training Systems competition.
Google Proposes Lasso Algorithm Variant for Learning Convolutions: ‘Bridging the Gap Between Fully-Connected and Convolutional Nets’
Unlike previous work that suggested fully-connected networks can only deliver subpar performance, Neyshabur’s experiments showed a significant performance jump.
Asia China Computer Vision & Graphics Health Machine Learning & Data Science Research Shenzhen Institute of Advanced Technology
About Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
SIAT aims to enhance the innovative capacity of the equipment manufacturing and service industries in the Guangdong-Hong Kong region, promote the development of emerging industries possessing their own proprietary intellectual property, and become a world-class industrial research institute.
SIAT Researchers Propose Novel Correction Method for Gas Sensor Drift Problem
Researchers developed a subspace learning-based domain adaptation method, which could potentially alleviate the gas sensor drift problem.
New White-Box Framework Will Cartoonize Your World
This framework can generate high-quality cartoonized images with much-improved controllability.
Adobe and Stanford Unveil SOTA Method for Human Pose Estimation
The researchers say the approach produces motions that are visually and physically much more plausible than state-of-the-art methods.
DeepMind’s AlignNet Learns Stable Object Representations Across Time
New research from UK based AI company and research lab DeepMind is enabling AI agents to perceive dynamic real-world environments more like humans do.
Microsoft & MIT Apply Adversarially Robust Models for Better Transfer Learning
Despite being less accurate on ImageNet, adversarially robust neural networks can match or improve their standard counterparts’ transfer performance.
Joint Spatial-Temporal Transformation Learning Boosts Video Inpainting Performance
Researchers introduce a joint Spatial-Temporal Transformer Network (STTN) to tackle such video inpainting challenges.
Facebook & Inria Propose High-Performance Self-Supervised Technique for CV Tasks
Researchers have developed a new technique for self-supervised training of convolutional networks used for image classification and other computer vision tasks.
Automating Machine Learning: Google AutoML-Zero Evolves ML Algorithms From Scratch
Google researchers propose an “AutoML-Zero” approach designed to automatically search for machine learning (ML) algorithms from scratch, requiring minimal human expertise or input.
Meet ByteDance AI’s Xiaomingbot: World’s First Multilingual and Multimodal AI News Agent
Researchers from ByteDance AILab and Shanghai Jiao Tong University have introduced Xiaomingbot, a multilingual and multimodal news reporter.
Fujitsu Develops World’s First AI technology to Accurately Capture Characteristics of High-Dimensional Data Without Labeled Training Data
Fujitsu has developed the world’s first AI technology that accurately captures the characteristics of high-dimensional data without labeled training data.
SIAT Researchers Propose Novel Deep Learning Method for Positron Emission Tomography
Researchers developed a novel deep learning method that reconstructs PET images using a cascading back-projection neural network (bpNet).
Google Bridges Domain Gaps in Semantic Segmentation of LiDAR Point Clouds
A team of Google researchers recently proposed a novel “complete and label” domain adaptation approach.
Grounded Language Learning: A Look at the Paper ‘Understanding Early Word Learning in Situated Artificial Agents’
This paper carefully engineers artificial-language learning experiments to replicate sources of information infants learn from and under what conditions.
NVIDIA Novel vid2vid Framework Synthesizes Realistic World-Consistent Videos
NVIDIA researchers propose a novel vid2vid framework that utilizes all past generated frames during rendering.
Popular Microsoft Chatbot XiaoIce Gains Independence as a New Company Led by Di Li and Harry Shum
Microsoft announced it would spin off its chatbot business XiaoIce, with all associated technologies licensed to a newly formed independent company.
ProtTrans Delivers SOTA Pretrained Language Models for Proteins
Researchers launched the ProtTrans Project, which provides an outstanding model for protein pretraining.
PLATO-2: The State-Of-The-Art Open-Domain Chatbot in Chinese and English
PLATO-2, a open-domain chatbot model, can talk about anything in Chinese and English and engage in deep conversations.
Facebook & CMU Introduce TaBERT for Understanding Tabular Data Queries
TaBERT-powered neural semantic parsers showed performance improvements on the challenging benchmark WikiTableQuestions and demonstrated competitive performance on the text-to-SQL dataset Spider.
Introducing TayPO, a Unifying Framework for Reinforcement Learning
Researchers proposed a Taylor Expansion Policy Optimization (TayPO) framework that combines two leading algorithmic improvement methods.
ICML 2020 Announces Outstanding Paper Awards
The acceptance rate of 21.8 percent is slightly lower than 2019’s 22.6 percent (774 accepted papers from 3,424 submissions).
DeepMind Explores Generalization and Efficiency in Algorithm Design
DeepMind introduced a new approach designed to improve the generalizability and efficiency of algorithms represented by neural networks.
New Google Research Incorporates Societal Context in ML Systems
To promote fairer ML systems, the team introduced a collaborative causal theory formation that incorporates diverse stakeholder perspectives for discovering and considering societal context.
DeepMind Explores Deep RL for Brain and Behaviour Research
DeepMind researchers call attention to another “fundamentally novel” development in AI research — deep reinforcement learning (deep RL) — which they believe also has vital implications for neuroscience and deserves more attention from neuroscientists.
Viral Post Highlights ‘Toxicity Problems’ in the Machine Learning Community
The post highlights perceived peer-review problems, the reproducibility crisis, and ethics and diversity issues.
Grand Theft Auto Scene Context Data Boosts Human Motion Prediction
A team of researchers proposed a novel three-stage learning framework that includes scene context to generate long-term 3D human motion prediction when given a single scene image and 2D pose histories.
Researchers Propose ‘Neuro-Symbolic’ Approach for Generative Art
Researchers propose a neuro-symbolic hybrid approach to address the challenge of creativity in generative art.
ACL 2020 Announces Best Paper & Test-Of-Time Awards
Organizers of the 58th Annual Meeting of the Association for Computational Linguistics (ACL) today announced their Best Paper Awards.
‘Beyond the ConvNet’ -Stanford & MIT Neural Network Learns Physical Graph Representations from Video
Researchers introduce a novel Physical Scene Graphs (PSG) approach designed to obtain a better structured understanding of visual scenes.
Facebook Introduces Integrated Eye & Face Model for 3D Immersion in Remote Communication
The proposed method generalizes well across various degrees of eye openness, different identities, and combinations of eye and lower facial expressions.