Haims Capital, a financial technology firm specializing in data-driven investment analytics, announced plans to launch RKM ...

Abstract: Multi-kernel clustering aims to learn a fused kernel from a set of base kernels. However, conventional multi-kernel clustering methods typically suffer from inherent limitations in ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Abstract: Multi-kernel learning is an excellent machine learning algorithm widely used in various learning tasks such as classification and regression. Traditional kernel methods mainly focus on ...

Selecting more sustainable solvents is a crucial component to mitigating the environmental impacts of chemical processes. Numerous tools have been developed to address this problem within the ...

Workflow of the Fisher kernel prediction approach. To generate a description of brain dynamics, we (1) concatenate all subjects’ individual timeseries; then (2) estimate a Hidden Markov Model (HMM) on ...

I was writing a Triton kernel to cast fp16 to fp8, which is used in llama 70B model. The kernel was fine with not-so-large matrix but was getting memory access fault with large shapes like (40960, ...

When trying to add a printer to your Windows computer, you may encounter an error that says Windows can’t install the kernel-mode print driver. This just means that ...