INNOVATION

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Eleven Multilingual v1: New Speech Synthesis Model Introduced

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@miketamir

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18 May 2023 21h01

Introducing Eleven Multilingual v1: Our New Speech Synthesis Model https://
bit.ly/3Nou3Rr #AI #MachineLearning #LLMs #deeplearning

Simulants: AI Method Synthesizes Privacy-Preserving Clinical Trial Data

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18 May 2023 20h53

"Simulants" is a method for synthesizing clinical trial data that maintains subject privacy, facilitating data sharing and innovation in fields like drug safety and bias analysis. Submitted by: Afrah Shafquat @Medidata

JoinBoost: SQL-based tree model training library

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18 May 2023 20h53

"JoinBoost" is a Python library that enables the training of tree models on normalized databases using pure SQL queries, offering portability, scalability, and competitive performance. Submitted by: Zachary Huang @Columbia

Compressed NLP Models: Cost-Effective LLM Deployment Alternative

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18 May 2023 20h53

"Why smaller specialized NLP models might be the secret to easier LLM deployment" proposes the use of compressed NLP models as a cost-effective & efficient alternative to #LLMs, with similar performance but significantly reduced deployment challenges. By: Meryem Arik @titanML

Minimax Optimal Stability Estimation Under Distribution Shift

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18 May 2023 20h53

"Minimax Optimal Estimation of Stability Under Distribution Shift" this study proposes an estimator for gauging system stability under environmental changes, providing a method to predict performance deterioration and ensure robustness. Submitted by: Yuanzhe Ma @Columbia

FILA: Optimal Online Auditing Technique for ML Model Accuracy

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18 May 2023 20h53

"FILA" is an optimal online auditing technique for ML model accuracy that uses a sampling-based approach and Thompson Sampling to estimate accuracy under a finite labeling budget. Submitted by: Naiqing Guan @UofT

Nonlinear Dimensionality Reduction for Fluid Flow Modeling

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18 May 2023 20h53

"Comparing nonlinear dimensionality reduction for data-driven unsteady fluid flow modeling" explores various NDR techniques, ie manifold learning & deep learning, noting superior spatial reconstruction & physically interpretable modes. Submitted by: Hunor Csala @UUtah

Machine Learning Analyzes Climate Change Infrastructure Impacts

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18 May 2023 20h53

"Analyzing the impact of climate change on critical infrastructure from the scientific literature" uses a weakly supervised machine learning approach to efficiently analyze a large corpus of research on climate change impacts on infrastructure. By: Tanwi Mallick @argonne

Lossy Compression for Large Scientific Dataset Training

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18 May 2023 20h53

"The Bearable Lightness of Big Data" presents the use of lossy compression algorithms to reduce the size of large scientific datasets while maintaining data fidelity for training deep learning models. Submitted by: Wai Tong Chung @Stanford