RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the ...
A great point was raised on my last post about vector normalization — and it’s absolutely correct. When you normalize a vector, its length is always forced to 1. That’s perfect for direction, but it ...
CTO at Scorealytics.com, a legal-tech company. Also, a leader in the development of algorithms for Cognitive AI, and the use of RAG with AI. Also, hosts in-person NYC business leadership events, twice ...
Abstract: This paper investigates sample vector normalization as a statistical preprocessing technique for cooperative spectrum sensing under realistic direct-conversion receiver (DCR) impairments. A ...
--Copyright 2025 IST, University of Lisbon and INESC-ID. --SPDX-License-Identifier: Apache-2.0 WITH SHL-2.1 --Licensed under the Solderpad Hardware License v 2.1 (the ...
Currently, all sparse embeddings vectors are normalized just like dense vectors. The majority of SPLADE models were trained using dot product similarity with unnormalized vectors. This helps better ...
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