The objective of dataset condensation is to ensure that the model trained with the synthetic dataset can perform comparably to the model trained with full datasets. However, existing methods predominantly concentrate on classification tasks, posing challenges in their adaptation to time series forecasting (TS-forecasting).

Campaigners fear Narendra Modi could use AI to increase state surveillance and sway elections. Campaigners fear Narendra Modi could use AI to increase state surveillance and sway elections. Silicon Valley tech billionaires will land in Delhi this week for an AI summit hosted by India's prime minister, Narendra Modi, where leaders of the global south will wrestle for control over the fast-developing technology. During the week-long AI Impact Summit, attended by thousands of tech executives, government officials and AI safety experts, tech companies valued at trillions of dollars will rub along with leaders of countries such as Kenya and Indonesia, where average wages dip well below $1,000 a month. Amid a push to speed up AI adoption across the globe, Sundar Pichai, Sam Altman and Dario Amodei, the heads of Google, OpenAI and Anthropic, will all be there.

The synthetic datasets are expected to capture the essence of the knowledge contained in real-world datasets such that the former yields a similar performance as the latter.

Source code is available at https://github.com/MIV-XJTU/SPEED .

Using these smoothed rank andsort operators, we propose differentiable proxies for the classification 0/1 loss as well as for the quantileregressionloss.

Bayesian optimisation (BO) is a powerful framework for global optimisation of costly functions, using predictions from Gaussian process models (GPs).

There are still, however, some unsolved challenges for a successful deployment of RL such as efficient learning of constrained or safe Markov Decision Processes (MDPs) [4].