Daily Excelsior

Machine Learning Methods Used for Portfolio Optimization and Risk Management

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
GitHub

softmax_lse is silently not backpropogated

Another solution is to call ctx.set_materialize_grads(False) and then raise an exception in the backward function if the incoming grads are not None. Sign up for free to join this conversation on ...
IEEE

Hardware-Efficient SoftMax Architecture With Bit-Wise Exponentiation and Reciprocal Calculation

Abstract: The SoftMax function is one of the activation functions used in deep neural networks (DNN) to normalize input values to the range of (0,1). With the advent of DNN models including the ...
marktechpost

Enhancing Artificial Intelligence Reasoning by Addressing Softmax Limitations in Sharp Decision-Making with Adaptive Temperature Techniques

The ability to generate accurate conclusions based on data inputs is essential for strong reasoning and dependable performance in Artificial Intelligence (AI) systems. The softmax function is a ...
marktechpost

FlashSigmoid: A Hardware-Aware and Memory-Efficient Implementation of Sigmoid Attention Yielding a 17% Inference Kernel Speed-Up over FlashAttention-2 on H100 GPUs

Large Language Models (LLMs) have gained significant prominence in modern machine learning, largely due to the attention mechanism. This mechanism employs a sequence-to-sequence mapping to construct ...