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

Abciximab‐Associated Thrombocytopenia After Previous Tirofiban‐Related Thrombocytopenia

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90080/1/phco.26.3.423.pd

BAIT: Benchmarking (Embedding) Architectures for Interactive Theorem-Proving

Artificial Intelligence for Theorem Proving has given rise to a plethora of benchmarks and methodologies, particularly in Interactive Theorem Proving (ITP). Research in the area is fragmented, with a diverse set of approaches being spread across several ITP systems. This presents a significant challenge to the comparison of methods, which are often complex and difficult to replicate. Addressing this, we present BAIT, a framework for fair and streamlined comparison of learning approaches in ITP. We demonstrate BAIT's capabilities with an in-depth comparison, across several ITP benchmarks, of state-of-the-art architectures applied to the problem of formula embedding. We find that Structure Aware Transformers perform particularly well, improving on techniques associated with the original problem sets. BAIT also allows us to assess the end-to-end proving performance of systems built on interactive environments. This unified perspective reveals a novel end-to-end system that improves on prior work. We also provide a qualitative analysis, illustrating that improved performance is associated with more semantically-aware embeddings. By streamlining the implementation and comparison of Machine Learning algorithms in the ITP context, we anticipate BAIT will be a springboard for future research

Restocking Northern Bobwhites in East Texas: A Genetic Assessment

Habitat on a 610-ha study area in the Pineywoods Ecological Region of eastern Texas was enhanced for northern bobwhites ( Coli nus virginianus). In February and March 1990, 1991, and 1992, bobwhites from south Texas (C. v. texanus) and disjunct areas of east Texas (C. v. mexicanus) were captured, radio tagged, and relocated to the study area which had a small ( \u3c25 birds) resident population. Blood samples were collected from the birds relocated in 1991. Samples were also collected from birds in the resident population during 1991 and 1992; these birds were assumed to be offspring of the previous years\u27 resident and relocated bobwhites. Restriction site variation of mitochondrial DNA (mtDNA) revealed geographic subdivision between the subspecies but not between resident and east Texas relocated birds. The observed frequency differences of mtDNA haplotypes were used to assess the relative reproductive success of the 2 subspecies. Among the birds examined for mtDNA variation, offspring produced on the study area during 1990 and 1991 were genetically more similar to the east Texas subspecies than to the south Texas subspecies. These results suggest that efforts to restock northern bobwhite should involve either local birds or birds from the same subspecies. Management implications of these findings are discussed

Translational potential of long-term decreases in mitochondrial lipids in a mouse model of Gulf War Illness

Gulf War Illness (GWI) affects 25% of veterans from the 1990–1991 Gulf War (GW) and is accompanied by damage to the brain regions involved in memory processing. After twenty-five years, the chronic pathobiology of GWI is still unexplained. To address this problem, we examined the long-term consequences of GW exposures in an established GWI mouse model to identify biological processes that are relevant to the chronic symptoms of GWI. Three-month old male C57BL6 mice were exposed for 10 days to GW agents (pyridostigmine bromide and permethrin). Barnes Maze testing conducted at 15- and 16-months post-exposure revealed learning and memory impairment. Immunohistochemical analyses showed astroglia and microglia activation in the hippocampi of exposed mice. Proteomic studies identified perturbation of mitochondria function and metabolomics data showed decreases in the Krebs cycle compounds, lactate, β-hydroxybutyrate and glycerol-3 phosphate in the brains of exposed mice. Lipidomics data showed decreases in fatty acids, acylcarnitines and phospholipids, including cardiolipins in the brains of exposed mice. Pilot biomarker studies showed that plasma from exposed mice and veterans with GWI had increases in odd-chain, and decreases in long-chain, acylcarnitines compared to their respective controls. Very long-chain acylcarnitines were decreased in veterans with GWI compared to controls. These studies suggest that mitochondrial lipid disturbances might be associated with GWI and that further investigation is required to determine its role in the pathophysiology of this illness. Targeting mitochondrial function may provide effective therapies for GWI, and that lipid abnormalities could serve as biomarkers of GWI