Inefficiency of K-FAC for Large Batch Size Training

In stochastic optimization, using large batch sizes during training can leverage parallel resources to produce faster wall-clock training times per training epoch. However, for both training loss and testing error, recent results analyzing large batch Stochastic Gradient Descent (SGD) have found sharp diminishing returns, beyond a certain critical batch size. In the hopes of addressing this, it has been suggested that the Kronecker-Factored Approximate Curvature (\mbox{K-FAC}) method allows for greater scalability to large batch sizes, for non-convex machine learning problems such as neural network optimization, as well as greater robustness to variation in model hyperparameters. Here, we perform a detailed empirical analysis of large batch size training %of these two hypotheses, for both \mbox{K-FAC} and SGD, evaluating performance in terms of both wall-clock time and aggregate computational cost. Our main results are twofold: first, we find that both \mbox{K-FAC} and SGD doesn't have ideal scalability behavior beyond a certain batch size, and that \mbox{K-FAC} does not exhibit improved large-batch scalability behavior, as compared to SGD; and second, we find that \mbox{K-FAC}, in addition to requiring more hyperparameters to tune, suffers from similar hyperparameter sensitivity behavior as does SGD. We discuss extensive results using ResNet and AlexNet on \mbox{CIFAR-10} and SVHN, respectively, as well as more general implications of our findings

The post-Paris approach to mitigating Arctic warming—perspectives from shipping emissions reduction

The availability of increased Arctic shipping as a consequence of sea ice decline is a regional issue that is closely linked with international climate governance and global governance of the maritime industry. Sea ice decline creates favorable circumstances for the development of merchant shipping, but is accompanied by increases in greenhouse gas emissions. Reduction of greenhouse gas emissions from the shipping industry is of utmost importance to prevent the destruction of the fragile Arctic ecosystem. This paper focuses on the core content of the Paris Agreement and suggests that the International Maritime Organization could guide the shipping industry to reach a fair agreement with states that includes market-based measures, capacity building, and voluntary actions of shipping companies as non-state actors

DreamTalk: When Expressive Talking Head Generation Meets Diffusion Probabilistic Models

Diffusion models have shown remarkable success in a variety of downstream generative tasks, yet remain under-explored in the important and challenging expressive talking head generation. In this work, we propose a DreamTalk framework to fulfill this gap, which employs meticulous design to unlock the potential of diffusion models in generating expressive talking heads. Specifically, DreamTalk consists of three crucial components: a denoising network, a style-aware lip expert, and a style predictor. The diffusion-based denoising network is able to consistently synthesize high-quality audio-driven face motions across diverse expressions. To enhance the expressiveness and accuracy of lip motions, we introduce a style-aware lip expert that can guide lip-sync while being mindful of the speaking styles. To eliminate the need for expression reference video or text, an extra diffusion-based style predictor is utilized to predict the target expression directly from the audio. By this means, DreamTalk can harness powerful diffusion models to generate expressive faces effectively and reduce the reliance on expensive style references. Experimental results demonstrate that DreamTalk is capable of generating photo-realistic talking faces with diverse speaking styles and achieving accurate lip motions, surpassing existing state-of-the-art counterparts.Comment: Project Page: https://dreamtalk-project.github.i

A novel method of rapid detection for heavy metal copper ion via a specific copper chelator bathocuproinedisulfonic acid disodium salt

The extensive usage and production of copper may lead to toxic effects in organisms due to its accumulation in the environment. Traditional methods for copper detection are time consuming and infeasible for field usage. It is necessary to discover a real-time, rapid and economical method for detecting copper to ensure human health and environmental safety. Here we developed a colorimetric paper strip method and optimized spectrum method for rapid detection of copper ion based on the specific copper chelator bathocuproinedisulfonic acid disodium salt (BCS). Both biological assays and chemical methods verified the specificity of BCS for copper. The optimized reaction conditions were 50 mM Tris–HCl pH 7.4, 200 μM BCS, 1 mM ascorbate and less than 50 μM copper. The detection limit of the copper paper strip test was 0.5 mg/L by direct visual observation and the detection time was less than 1 min. The detection results of grape, peach, apple, spinach and cabbage by the optimized spectrum method were 0.91 μg/g, 0.87 μg/g, 0.19 μg/g, 1.37 μg/g and 0.39 μg/g, respectively. The paper strip assays showed that the copper contents of grape, peach, apple, spinach and cabbage were 0.8 mg/L, 0.9 mg/L, 0.2 mg/L, 1.3 mg/L and 0.5 mg/L, respectively. These results correlated well with those determined by inductively coupled plasma-mass spectrometry (ICP-MS). The visual detection limit of the paper strip based on Cu-BCS-AgNPs was 0.06 mg/L. Our study demonstrates the potential for on-site, rapid and cost-effective copper monitoring of foods and the environment

COMPUTE N-WAY DE-DUPLICATED REACH USING PRIVACY SAFE VECTOR OF COUNTS

Systems and methods for determining the union of the set of user identifiers across multiple publishers are described. Each publisher computing device can use a list of hash functions to hash the respective set of de-duplicated user identifiers. Each publisher can assemble a vector of counts using the respective hashed set of user identifiers, where each coordinate in the vector of counts corresponds to a select of bit positions from the hashed set of user identifiers. Each publisher can add noise to each of the vector of counts to enhance the privacy of the system. Each publisher can transmit the respective vector of counts to a server to compute the union of the multiset without exposing any private or protected information about the user identifiers to any third-party. The server can compute the union of the sets described by the vectors of counts from each of the publishers using at least one of the methods described herein