Self-directed learning Sacky Iipinge With a rapidly changing job market where technology and innovation are determining the future of work, adaptability is becoming a key driver of success.More ...

Using reinforcement learning, agentic AI can predict potential failures, such as hardware degradation or network congestion, ...

In recent years, neural architecture-based recommender systems have achieved tremendous success, but they still fall short of expectation when dealing with highly sparse data. Self-supervised learning ...

In this paper, we tackle for the first time, the problem of self-supervised representation learning for free-hand sketches. This importantly addresses a common problem faced by the sketch community – ...