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Found 9 papers, 3 papers with code
Near-Optimal Experimental Design Under the Budget Constraint in Online Platforms
A/B testing, or controlled experiments, is the gold standard approach to causally compare the performance of algorithms on online platforms.
Dynamic Budget Throttling in Repeated Second-Price Auctions
In the stochastic case, we illustrate that pacing is generally better than throttling for the buyer, which is an extension of known results that pacing is asymptotically optimal in this scenario.
Improved Lyman Alpha Tomography using Optimized Reconstruction with Constraints on Absorption (ORCA)
In this work, we propose an improved approach to reconstruct the three-dimensional intergalactic medium from observed Lyman-$\alpha$ forest absorption features.
Astrophysics of Galaxies
Spatial AMR: Expanded Spatial Annotation in the Context of a Grounded Minecraft Corpus
This paper presents an expansion to the Abstract Meaning Representation (AMR) annotation schema that captures fine-grained semantically and pragmatically derived spatial information in grounded corpora.
Towards Near-imperceptible Steganographic Text
We show that the imperceptibility of several existing linguistic steganographic systems (Fang et al., 2017; Yang et al., 2018) relies on implicit assumptions on statistical behaviors of fluent text.
Deep Learning of Quasar Spectra to Discover and Characterize Damped Lya Systems
Testing on a held-back validation set demonstrates a high incidence of DLAs recovered by the algorithm (97. 4% as DLAs and 99% as an HI absorber with log NHI > 19. 5) and excellent estimates for zabs and NHI.
Astrophysics of Galaxies
Glyph-aware Embedding of Chinese Characters
Given the advantage and recent success of English character-level and subword-unit models in several NLP tasks, we consider the equivalent modeling problem for Chinese.
Pay Attention to the Ending:Strong Neural Baselines for the ROC Story Cloze Task
We consider the ROC story cloze task (Mostafazadeh et al., 2016) and present several findings.
Video (GIF) Sentiment Analysis using Large-Scale Mid-Level Ontology
However, GIF sentiment analysis is quite challenging, not only because it hinges on spatio-temporal visual contentabstraction, but also for the relationship between such abstraction and final sentiment remains unknown. In this paper, we dedicated to find out such relationship. We proposed a SentiPairSequence basedspatiotemporal visual sentiment ontology, which forms the midlevel representations for GIFsentiment.
