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AAAI 2020 | A Turning Point for Deep Learning?

AAAI 2020 | A Turning Point for Deep Learning?

Geoffrey Hinton, Yann LeCun, and Yoshua Bengio shared a stage in New York on Sunday night at an event organized by AAAI 2020.
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Visualize Your Debugging! New Microsoft Toolkit Identifies and Diagnoses ML Model Errors

Visualize Your Debugging! New Microsoft Toolkit Identifies and Diagnoses ML Model Errors

Imagine an autonomous vehicle traffic sign detector whose accuracy plummets when dealing with rain or unexpected inputs. With machine…
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BENDR for BCI: UToronto’s BERT-Inspired DNN Training Approach Learns From Unlabelled EEG Data

BENDR for BCI: UToronto’s BERT-Inspired DNN Training Approach Learns From Unlabelled EEG Data

From predictive text to smart voice control, human-machine interfaces have been significantly improved in recent years. Many scientists…
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Apple Reveals Design of Its On-Device ML System for Federated Evaluation and Tuning

Apple Reveals Design of Its On-Device ML System for Federated Evaluation and Tuning

Apple has revealed system design details for its federated task processing system, demonstrating the potential of federated evaluation and…
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Google & JHU Paper Explores and Categorizes Neural Scaling Laws

Google & JHU Paper Explores and Categorizes Neural Scaling Laws

It is widely believed in the deep learning community that growing training sets and model size should improve performance. It is therefore…
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Yann LeCun Hails MSA Transformer’s ‘Huge Progress’ in Protein Contact Prediction

Yann LeCun Hails MSA Transformer’s ‘Huge Progress’ in Protein Contact Prediction

A transformer-based model that achieves state-of-the-art performance on unsupervised protein structure learning is making waves, with…
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UC Berkeley & Google’s BoTNet Applies Self-Attention to CV Bottlenecks

UC Berkeley & Google’s BoTNet Applies Self-Attention to CV Bottlenecks

Researchers from UC Berkeley and Google Research have introduced BoTNet, a “conceptually simple yet powerful” backbone architecture that…
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DeepMind Achieves High-Performance Large-Scale Image Recognition Without Batch Normalization

DeepMind Achieves High-Performance Large-Scale Image Recognition Without Batch Normalization

New research from UK-based Google subsidiary DeepMind demonstrates for the first time that image recognition models can be trained without…
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Stanford University Deep Evolutionary RL Framework Demonstrates Embodied Intelligence via Learning…

Stanford University Deep Evolutionary RL Framework Demonstrates Embodied Intelligence via Learning…

Stanford University researchers have proposed DERL (Deep Evolutionary Reinforcement Learning), a novel computational framework that…
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ICMI 2020 Best Paper | Gesticulator: A framework for semantically-aware speech-driven gesture…

ICMI 2020 Best Paper | Gesticulator: A framework for semantically-aware speech-driven gesture…

Content provided by Taras Kucherenko, first author of the paper Gesticulator: A framework for semantically-aware speech-driven gesture…
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