Reduce on-CPU prediction and model storage costs by zeroing-out weights while minimally increasing the loss.

Article URL: https://www.w3.org/TR/webnn/ Comments URL: https://news.ycombinator.com/item?id=36158663 Points: 1 # Comments: 0

Posted in r/MachineLearning by u/TryToExplainHow • 7 points and 18 comments

Neural networks are the fundamental components of deep learning techniques, and these are the most important topics in this field. Deep learning is a sub-branch of machine learning, and it dea...

Training algorithms, broadly construed, are an essential part of every deep learning pipeline. Training algorithm improvements that speed up training across a wide variety of workloads (e.g., better update rules, tuning protocols, learning rate schedules, or data selection schemes) could save time, save computational resources, and lead to better, more accurate, models. Unfortunately, as a community, we are…

Article URL: https://madebyoll.in./posts/game_emulation_via_dnn/ Comments URL: https://news.ycombinator.com/item?id=32730943 Points: 1 # Comments: 0

As deep neural networks (DNNs) grow to solve increasingly complex problems, they are becoming limited by the latency and power consumption of existing digital processors. 'Weight-stationary' analog optical and electronic hardware has been proposed to reduce the compute resources required by DNNs by eliminating expensive weight updates; however, with scalability limited to an input vector length $K$ of hundreds of…

tldr; I attempted to repeat my success with the evolving race cars by using evolutionary algorithms and neural networks to control simulated traffic flow in a segment of Chicago's streets. The results were… not so great. You can see associated code here. What is this? The tiny ant-like pixels running around above are emulated cars, running through a grid system generated from a rip of a small part of the city of…

There are about one million known species of insects - more than for any other group of living organisms. If you need to determine which species an insect belongs to, things get complicated quick. In ...

By modifying a classical neural network, researchers have introduced a new model inspired by recent biological findings which shows improved memory performance

Article URL: https://en.wikipedia.org/wiki/Efficiently_updatable_neural_network Comments URL: https://news.ycombinator.com/item?id=34470927 Points: 1 # Comments: 0

... dedicated to finding the Omega Pringle

Sarcasm Detection has enjoyed great interest from the research community, however the task of predicting sarcasm in a text remains an elusive problem for machines. Past studies mostly make use of twitter datasets collected using hashtag based supervision but such datasets are noisy in terms of labels and language. To overcome these shortcoming, we introduce a new dataset which contains news headlines from a…

Neural network emulator for guitar amplifiers. Contribute to sdatkinson/neural-amp-modeler development by creating an account on GitHub.

Read more about the unique combination of software and hardware that powers the Sonos ecosystem. Welcome to our technology blog.

To classify the texts accurately, many machine learning techniques have been utilized in the field of Natural Language Processing (NLP). For many pattern classification applications, great success has been obtained when implemented with deep learning models rather than using ordinary machine learning techniques. Understanding the complex models and their respective relationships within the data determines the…

Inspired by microscopic worms, Liquid AI's founders developed a more adaptive, less energy-hungry kind of neural network. Now the MIT spin-off is revealing several new ultraefficient models.

Deep learning (DL) has recently changed the development of intelligent systems and is widely adopted in many real-life applications. Despite their various benefits and potentials, there is a high demand for DL processing in different computationally limited and energy-constrained devices. It is natural to study game-changing technologies such as Binary Neural Networks (BNN) to increase deep learning capabilities.…

Article URL: https://www.cs.cmu.edu/~aharley/vis/conv/ Comments URL: https://news.ycombinator.com/item?id=31971267 Points: 1 # Comments: 0

Researchers have recently proposed the concept of ionization integral (P-int) to quantify the strength of plasma effect. This is the first time that nonlinear effects have been quantified experimentally. Relevant results were published in Physical Review Research.