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Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions.

ML @ CMU

Our work further motivates novel directions for developing and evaluating tools to support human-ML interactions. Model explanations have been touted as crucial information to facilitate human-ML interactions in many real-world applications where end users make decisions informed by ML predictions.

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Inductive biases of neural network modularity in spatial navigation

ML @ CMU

In practice, our algorithm is off-policy and incorporates mechanisms such as two critic networks and target networks as in TD3 ( fujimoto et al., 2020 ) to systematically quantify behavioral accuracy. 2018 ) to enhance training (see Materials and Methods in Zhang et al.,

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[AI/ML] Keswani’s Algorithm for 2-player Non-Convex Min-Max Optimization

Towards AI

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

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ML Collaboration: Best Practices From 4 ML Teams

The MLOps Blog

The onset of the pandemic has triggered a rapid increase in the demand and adoption of ML technology. Building ML team Following the surge in ML use cases that have the potential to transform business, the leaders are making a significant investment in ML collaboration, building teams that can deliver the promise of machine learning.

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Pioneering computer vision: Aleksandr Timashov, ML developer

Dataconomy

Aleksandr Timashov is an ML Engineer with over a decade of experience in AI and Machine Learning. I led several projects that dramatically advanced the company’s technological capabilities: Real-time Video Analytics for Security: We developed an advanced system integrating deep learning algorithms with existing CCTV infrastructure.

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Master Data Annotation in LLMs: A Key to Smarter and Powerful AI!

Data Science Dojo

These models are trained using vast datasets and powered by sophisticated algorithms. billion in 2020 to $4.1 Data annotation is the process of labeling data to make it understandable and usable for machine learning (ML) models. billion by 2025.

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KDnuggets™ News 20:n12, Mar 25: 24 Best (and Free) Books To Understand Machine Learning; Coronavirus Daily Change and Poll Analysis; 9 lessons learned during 1st year as a Data Scientist

KDnuggets

Read our analysis of coronavirus data and poll results; Use your time indoors to learn with 24 best and free books to understand Machine Learning; Study the 9 important lessons from the first year as a Data Scientist; Understand the SVM, a top ML algorithm; check a comprehensive list of AI resources for online learning; and more.