Review of non-separable binary classification and its applications in anomaly detection
The inability to linearly XOR classify has motivated much of deep learning. We revisit this old problem and show that ...
Tag: binary
Binary Classification. Unpacking the Real Significance and… | by gabriel costa
Unpacking the Real Significance and Limitations of Traditional MetricsThe work of classification can be seen as a way of summarizing ...
Bridging the Binary Gap: Challenges in Training Neural Networks to Decode and Summarize Code
The research area of this study is artificial intelligence (ai) and machine learning, specifically focusing on neural networks that can ...
MixedBread AI introduces Binary MRL: a novel embedding compression method that makes vector search scalable and enables embedding-based applications
Recently introduced Mixedbread.ai ai/mxbai-embed-large-v1">Binary MRL, a 64-byte embedding to address the challenge of scaling embeddings in natural language processing (NLP) ...
Meet BiLLM: a novel post-training binary quantization method designed specifically to compress pre-trained LLMs
Pretrained large language models (LLMs) have remarkable language processing capabilities, but require substantial computational resources. Binarization, which reduces model weights ...
Google Foobar Challenge: Level 3. Exploring binary, dynamic numbers… | by Katy Hagerty | November 2023
Exploring binary numbers, dynamic programming and Markov chainsPhoto by Rajeshwar Bachu in unpackThe Foobar Challenge is a coding challenge hosted ...
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