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5. You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling

Author

Zeng, Zhanpeng, Xiong, Yunyang, Ravi, Sathya N., Acharya, Shailesh, Fung, Glenn, and Singh, Vikas

Subjects
Computer Science - Machine Learning, Computer Science - Computation and Language
Abstract

Transformer-based models are widely used in natural language processing (NLP). Central to the transformer model is the self-attention mechanism, which captures the interactions of token pairs in the input sequences and depends quadratically on the sequence length. Training such models on longer sequences is expensive. In this paper, we show that a Bernoulli sampling attention mechanism based on Locality Sensitive Hashing (LSH), decreases the quadratic complexity of such models to linear. We bypass the quadratic cost by considering self-attention as a sum of individual tokens associated with Bernoulli random variables that can, in principle, be sampled at once by a single hash (although in practice, this number may be a small constant). This leads to an efficient sampling scheme to estimate self-attention which relies on specific modifications of LSH (to enable deployment on GPU architectures). We evaluate our algorithm on the GLUE benchmark with standard 512 sequence length where we see favorable performance relative to a standard pretrained Transformer. On the Long Range Arena (LRA) benchmark, for evaluating performance on long sequences, our method achieves results consistent with softmax self-attention but with sizable speed-ups and memory savings and often outperforms other efficient self-attention methods. Our code is available at https://github.com/mlpen/YOSO, Comment: Proceedings of the 38th ICML (2021)

Published
2021

6. Transcriptional Changes during Phytophthora capsici Infection Reveal Potential Defense Mechanisms in Squash.

Author

Acharya, Shailesh Raj, Shrestha, Swati, Michael, Vincent Njung'e, Fu, Yuqing, Sabharwal, Prerna, Thakur, Shallu, and Meru, Geoffrey

Subjects
*PHYTOPHTHORA capsici, *SQUASHES, *PEPTIDASE, *RNA sequencing, *PEROXIDASE
Abstract

Phytophthora capsici incites foliar blight, root, fruit, and crown rot in squash (Cucurbita spp.) and limits production worldwide. Resistance to crown rot in C. moschata breeding line #394-1-27-12 is conferred by three dominant genes, but the molecular mechanisms underlying this resistance are poorly understood. In the current study, RNA sequencing was used to investigate transcriptional changes in #394-1-27-12 (resistant) and Butterbush (susceptible) following infection by P. capsici at 12, 24, 48, 72, and 120 h post inoculation (hpi). Overall, the number of differentially expressed genes (DEGs) in Butterbush (2648) exceeded those in #394-1-27-12 (1729), but in both genotypes, the highest number of DEGs was observed at 72 hpi and least at 24 hpi. Our gene ontology (GO) analysis revealed a downregulation of the genes involved in polysaccharide and lignin metabolism in Butterbush but as an upregulation of those associated with regulation of peptidase activity. However, in #394-1-27-12, the downregulated genes were primarily associated with response to stimuli, whereas those upregulated were involved in oxidation–reduction and response to stress. The upregulated genes in #394-1-27-12 included defensin-like proteins, respiratory-burst oxidases, ethylene-responsive transcription factors, cytochrome P450 proteins, and peroxidases. These findings provide a framework for the functional validation of the molecular mechanisms underlying resistance to P. capsici in cucurbits. [ABSTRACT FROM AUTHOR]

Published
2023
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11. PHYSICO-CHEMICAL ANALYSIS OF SELECTED AGRICULTURAL SOIL SAMPLES IN JUNNAR TEHSIL OF PUNE DISTRICT, MAHARASHTRA.

Author

ACHARYA, SHAILESH M.

Subjects
SOIL sampling, SOIL acidity, BUSINESS schools, ORGANIC compounds, POTASSIUM
Abstract

An experiment was undertaken at College of Agriculture Business Management, Narayangaon Maharashtra to investigate the physico-chemical properties of Onion and Tomato soil at ten different sites of Junnar tehsil of Pune District during February 2018 to May 2019. The soil parameters like soil pH, EC, Organic Carbon, Nitrogen, Potassium and Phosphorous content were analyzed. It was found that there was a marked variation in nutrients and parameters of various sample point in different farmers field. The results of the study show the low levels of Nitrogen, Phosphorous and Potassium in both sites. Also the organic matter is low during the study area. [ABSTRACT FROM AUTHOR]

Published
2020

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