474 research outputs found

    Analogy Training Multilingual Encoders

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    Language encoders encode words and phrases in ways that capture their local semantic relatedness, but are known to be globally inconsistent. Global inconsistency can seemingly be corrected for, in part, by leveraging signals from knowledge bases, but previous results are partial and limited to monolingual English encoders. We extract a large-scale multilingual, multi-word analogy dataset from Wikidata for diagnosing and correcting for global inconsistencies and implement a four-way Siamese BERT architecture for grounding multilingual BERT (mBERT) in Wikidata through analogy training. We show that analogy training not only improves the global consistency of mBERT, as well as the isomorphism of language-specific subspaces, but also leads to significant gains on downstream tasks such as bilingual dictionary induction and sentence retrieval

    Large-scale distributions of tropospheric nitric, formic, and acetic acids over the western Pacific basin during wintertime

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    We report here measurements of the acidic gases nitric (HNO3), formic (HCOOH), and acetic (CH3COOH) over the western Pacific basin during the February-March 1994 Pacific Exploratory Mission-West (PEM-West B). These data were obtained aboard the NASA DC-8 research aircraft as it flew missions in the altitude range of 0.3–12.5 km over equatorial regions near Guam and then further westward encompassing the entire Pacific Rim arc. Aged marine air over the equatorial Pacific generally exhibited mixing ratios of acidic gases \u3c100 parts per trillion by volume (pptv). Near the Asian continent, discrete plumes encountered below 6 km altitude contained up to 8 parts per billion by volume (ppbv) HNO3 and 10 ppbv HCOOH and CH3COOH. Overall there was a general correlation between mixing ratios of acidic gases with those of CO, C2H2, and C2Cl4, indicative of emissions from combustion and industrial sources. The latitudinal distributions of HNO3 and CO showed that the largest mixing ratios were centered around 15°N, while HCOOH, CH3COOH, and C2Cl4 peaked at 25°N. The mixing ratios of HCOOH and CH3COOH were highly correlated (r2 = 0.87) below 6 km altitude, with a slope (0.89) characteristic of the nongrowing season at midlatitudes in the northern hemisphere. Above 6 km altitude, HCOOH and CH3COOH were marginally correlated (r2 = 0.50), and plumes well defined by CO, C2H2, and C2Cl4 were depleted in acidic gases, most likely due to scavenging during vertical transport of air masses through convective cloud systems over the Asian continent. In stratospheric air masses, HNO3 mixing ratios were several parts per billion by volume (ppbv), yielding relationships with O3 and N2O consistent with those previously reported for NOy

    Le Chatelier principle in replicator dynamics

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    The Le Chatelier principle states that physical equilibria are not only stable, but they also resist external perturbations via short-time negative-feedback mechanisms: a perturbation induces processes tending to diminish its results. The principle has deep roots, e.g., in thermodynamics it is closely related to the second law and the positivity of the entropy production. Here we study the applicability of the Le Chatelier principle to evolutionary game theory, i.e., to perturbations of a Nash equilibrium within the replicator dynamics. We show that the principle can be reformulated as a majorization relation. This defines a stability notion that generalizes the concept of evolutionary stability. We determine criteria for a Nash equilibrium to satisfy the Le Chatelier principle and relate them to mutualistic interactions (game-theoretical anticoordination) showing in which sense mutualistic replicators can be more stable than (say) competing ones. There are globally stable Nash equilibria, where the Le Chatelier principle is violated even locally: in contrast to the thermodynamic equilibrium a Nash equilibrium can amplify small perturbations, though both this type of equilibria satisfy the detailed balance condition.Comment: 12 pages, 3 figure

    Evaluating regional emission estimates using the TRACE-P observations

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    Measurements obtained during the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) experiment are used in conjunction with regional modeling analysis to evaluate emission estimates for Asia. A comparison between the modeled values and the observations is one method to evaluate emissions. Based on such analysis it is concluded that the inventory performs well for the light alkanes, CO, ethyne, SO2, and NOₓ. Furthermore, based on model skill in predicting important photochemical species such as O₃, HCHO, OH, HO₂, and HNO₃, it is found that the emissions inventories are of sufficient quality to support preliminary studies of ozone production. These are important finding in light of the fact that emission estimates for many species (such as speciated NMHCs and BC) for this region have only recently been estimated and are highly uncertain. Using a classification of the measurements built upon trajectory analysis, we compare observed species distributions and ratios of species to those modeled and to ratios estimated from the emissions inventory. It is shown that this technique can reconstruct a spatial distribution of propane/benzene that looks remarkably similar to that calculated from the emissions inventory. A major discrepancy between modeled and observed behavior is found in the Yellow Sea, where modeled values are systematically underpredicted. The integrated analysis suggests that this may be related to an underestimation of emissions from the domestic sector. The emission is further tested by comparing observed and measured species ratios in identified megacity plumes. Many of the model derived ratios (e.g., BC/CO, SOₓ/C₂H₂) fall within ∼25% of those observed and all fall outside of a factor of 2.5. (See Article file for details of the abstract.)Department of Civil and Environmental EngineeringAuthor name used in this publication: Wang, T

    Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games

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    We introduce a new approach for computing optimal equilibria and mechanisms via learning in games. It applies to extensive-form settings with any number of players, including mechanism design, information design, and solution concepts such as correlated, communication, and certification equilibria. We observe that optimal equilibria are minimax equilibrium strategies of a player in an extensive-form zero-sum game. This reformulation allows us to apply techniques for learning in zero-sum games, yielding the first learning dynamics that converge to optimal equilibria, not only in empirical averages, but also in iterates. We demonstrate the practical scalability and flexibility of our approach by attaining state-of-the-art performance in benchmark tabular games, and by computing an optimal mechanism for a sequential auction design problem using deep reinforcement learning
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