Machine Learning

Latest Computer Vision Research at Nanyang Technological University Introduces VToonify Framework for Style Controllable High-Resolution Video Toonification

Artistic portraits are everywhere in their everyday lives and in the creative sectors that inform the arts, social media avatars, movies, entertainment advertising, etc....

Researchers Developed SmoothNets For Optimizing Convolutional Neural Network (CNN) Architecture Design For Differentially Private Deep Learning

Differential privacy (DP) is used in machine learning to preserve the confidentiality of the information that forms the dataset. The most used algorithm to...

Google AI Introduces A Novel Reinforcement Learning (RL) Training Paradigm, ‘ActorQ,’ To Speed Up Actor-Learner Distributed RL Training

Several sequential decision-making challenges, like robotics, gaming, nuclear physics, balloon navigation, etc., have been successfully addressed using deep reinforcement learning. However, despite its potential,...

Microsoft Announces The Release Of Their Two Billion Parameter Latest Vision-Language AI Model Called BEiT-3

Microsoft's Natural Language Computing (NLC) team recently introduced their latest vision-language AI model, BEiT-3, a Bidirectional Encoder representation from Image Transformers with 1.9 billion...

Deepmind Introduces ‘Sparrow,’ An Artificial Intelligence-Powered Chatbot Developed To Build Safer Machine Learning Systems

Technological advancements strive to develop AI models that communicate more efficiently, accurately, and safely. Large language models (LLMs) have achieved outstanding success in recent...

Researchers From China Construct A New GAN Adaption Framework For The Generalized One-Shot GAN Adaption Task

The Generative Adversarial Network (GAN) is a deep neural network architecture that may learn from training data and produce new data that shares the...

A Primer on Data Labeling Approaches To Building Real-World Machine Learning Applications

Introductionā€ In computer vision and machine learning operations, data labeling is an essential part of the overall workflow. For reference, data labeling is the process...

Researchers Devise a Method for Permuting Model Units Whose Transformation Yields a Functionally Comparable Set of Weights in an Approximately Convex Basin Around the...

Deep learning's success is due to its capacity to tackle some enormous non-convex optimization problems with relative simplicity. Even though non-convex optimization is NP-hard,...

OpenAIĀ Releases Whisper: A New Open-Source Machine Learning Model For Multi-Lingual Automatic Speech Recognition

Using only an off-the-shelf transformer trained on 680,000 hours of weakly-supervised, multi-lingual audio data, OpenAIā€™s Whisper can approach human-level robustness and accuracy in ASR,...

Meet ‘AskEdith’: An Artificial Intelligence (AI) Powered English-To-SQL Translator That Lets You Work With Databases And Spreadsheets

Have you ever wished to "simply get the answer" when looking at an Excel sheet? Or that you could view your database structure without...

Researchers Propose a Feature-Space Video Coding Network (FVC) by Performing all Major Operations in the Feature Space

The constant improvement in display technologies and emerging new media representation types such as 360-degree videos enabled videos to have better visual characteristics such...

An Interview Study by UC Berkeley Researchers Explain the Process of Operationalizing Machine Learning or MLOps that Expose Variables that Govern the Success of...

As Machine Learning becomes increasingly prevalent in software, a new subfield known as MLOps (short for ML Operations) has evolved to organize the "collection...

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