AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers. (arXiv:1911.08097v1 [eess.SP])

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Low-precision arithmetic operations to accelerate deep-learning applications on field-programmable gate arrays (FPGAs) have been studied extensively, because they offer the potential to save silicon area or increase throughput. However, these benefits come at the cost of a decrease in accuracy. In this article, we demonstrate that reconfigurable constant coefficient multipliers (RCCMs) offer a better alternative…

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations. (arXiv:1911.07979v1 [cs.LG])

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Graph Neural Networks (GNN) have been shown to work effectively for modeling graph structured data to solve tasks such as node classification, link prediction and graph classification. There has been some recent progress in defining the notion of pooling in graphs whereby the model tries to generate a graph level representation by downsampling and summarizing…

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling. (arXiv:1911.07982v1 [cs.LG])

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Unsupervised domain adaptation aims to address the problem of classifying unlabeled samples from the target domain whilst labeled samples are only available from the source domain and the data distributions are different in these two domains. As a result, classifiers trained from labeled samples in the source domain suffer from significant performance drop when directly…

Multiple Testing of Local Extrema for Detection of Change Points. (arXiv:1504.06384v2 [math.ST] UPDATED)

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A new approach to detect change points based on differential smoothing and multiple testing is presented for long data sequences modeled as piecewise constant functions plus stationary ergodic Gaussian noise. As an application of the STEM algorithm for peak detection developed in \citet{schwartzman2011multiple} and \citet{cheng2017multiple}, the method detects change points as significant local maxima and…

Nothing to see here? Non-inferiority approaches to parallel trends and other model assumptions. (arXiv:1805.03273v3 [stat.ME] UPDATED)

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Many causal models make assumptions of “no difference” or “no effect.” For example, difference-in-differences (DID) assumes that there is no trend difference between treatment and comparison groups (“parallel trends”). Tests of these assumptions typically assume a null hypothesis that there is no violation. When researchers fail to reject the null, they consider the assumption to…

SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits. (arXiv:1809.08151v4 [cs.LG] UPDATED)

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Motivated by cognitive radio networks, we consider the stochastic multiplayer multi-armed bandit problem, where several players pull arms simultaneously and collisions occur if one of them is pulled by several players at the same stage. We present a decentralized algorithm that achieves the same performance as a centralized one, contradicting the existing lower bounds for…

Communication, Distortion, and Randomness in Metric Voting. (arXiv:1911.08129v1 [cs.GT])

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In distortion-based analysis of social choice rules over metric spaces, one assumes that all voters and candidates are jointly embedded in a common metric space. Voters rank candidates by non-decreasing distance. The mechanism, receiving only this ordinal (comparison) information, should select a candidate approximately minimizing the sum of distances from all voters. It is known…

A Multicriteria Macroeconomic Model with Intertemporal Equity and Spatial Spillovers. (arXiv:1911.08247v1 [econ.TH])

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We analyze a macroeconomic model with intergenerational equity considerations and spatial spillovers, which gives rise to a multicriteria optimization problem. Intergenerational equity requires to add in the definition of social welfare a long run sustainability criterion to the traditional discounted utilitarian criterion. The spatial structure allows for the possibility of heterogeneiity and spatial diffusion implies…