In this section, we provide the detailed description of the datasets we used to perform all the experimentsforCoMix,namely,(1)UCF-HMDB[3],(2)Jester[13],and(3)Epic-Kitchens[12].

Learning rate is a crucial parameter in training of neural networks. A properly tuned learning rate leads to faster training and higher test accuracy. In this paper, we propose a Lipschitz bandit-driven approach for tuning the learning rate of neural networks. The proposed approach is compared with the popular HyperOpt technique used extensively for hyperparameter optimization and the recently developed bandit-based algorithm BLiE. The results for multiple neural network architectures indicate that our method finds a better learning rate using a) fewer evaluations and b) lesser number of epochs per evaluation, when compared to both HyperOpt and BLiE. Thus, the proposed approach enables more efficient training of neural networks, leading to lower training time and lesser computational cost.

Right around the time Meta started making a feverish pitch for the headset-powered metaverse, executives at other tech companies began piping up to point out that the metaverse could already be accessed through hugely popular mobile apps like Fortnite and Roblox. People love these apps--especially kids and teens. Who needs a full-face computer when you can easily spend hours chatting with friends using the screens you already have? Now Roblox, which isn't just a game but an entire platform of user-generated video games, is adding more power to its metaverse punch. Starting in November, Roblox plans to launch an immersive video-chat option for gamers, Roblox chief executive David Baszucki said in an exclusive interview with WIRED ahead of the company's developers conference this week.

Recent developments in artificial intelligence and automation support a new drug design paradigm: autonomous drug design. Under this paradigm, generative models can provide suggestions on thousands of molecules with specific properties, and automated laboratories can potentially make, test and analyze molecules with minimal human supervision. However, since still only a limited number of molecules can be synthesized and tested, an obvious challenge is how to efficiently select among provided suggestions in a closed-loop system. We formulate this task as a stochastic multi-armed bandit problem with multiple plays, volatile arms and similarity information. To solve this task, we adapt previous work on multi-armed bandits to this setting, and compare our solution with random sampling, greedy selection and decaying-epsilon-greedy selection strategies. According to our simulation results, our approach has the potential to perform better exploration and exploitation of the chemical space for autonomous drug design.

Saving the bees is a worldwide concern. A significant share of our nutrition relies on the single efficient pollinator, the honey bee. While the honey bee is going rapidly extinct, we at Beewise create the solution: The BeeHome. The two main key factors for succeeding in doing that are people and technology. While we are dealing with multidisciplinary technology concerns, the heart that makes BeeHomes worldwide tick is AI.

Hey guys, this is Raj from thetechia.in But before I start I'll feel glad to inform you about the post we posted previously where we have discussed about the latest tech innovation regarding the smartphone back case that changes it's color with time and user's experience. So let's return to our today's topic of discussion about the comparison between cameras and eyes. So the first question that arises in this context is that when we observe or capture an object, we do a single task? During the above concerned question, why we fail in zooming to the object with our Normal eyes but succeed in the cameras.

In the quest to better understand climate change, there is plenty we still don't know. But the question isn't whether or not climate change is happening. "What we sometimes hear on the news is political manufactured uncertainty," said Auroop Ganguly, a professor of civil & environmental engineering at Northeastern. Instead, real climate change uncertainty stems from the challenge of simulating the future. What will happen to Boston's electric grid under long-term extreme weather conditions?

Delivery drones are just another brick in the automation wall that's hurtling towards us all. If (when) they come into popular use they have massive potential to disrupt current logistical methods across a number of industries. There are a whole bunch of pro's and con's, but at the rate they are being developed it seems that the broad mantra is that automated delivery, speed and convenience, even if there is a cost, is "what people want". The Brandwatch React team looked to social data to see if we could verify whether or not delivery drones were something people looked forward to experiencing or something, like autonomous cars, that's discussed with more skepticism. We tracked around 64,000 mentions of delivery drones, and related terms, across social media from 1 May to 27 June 2017. They fluctuated enormously by day, from 200 to 5,000 mentions, with spikes occurring when big news stories about developments occurred.