TD-SLIP: A better predictive model for human running



TD-gammon revisited: integrating invalid actions and dice factor in continuous action and observation space
Usta, Engin Deniz; Alpaslan, Ferda Nur; Department of Computer Engineering (2018)
After TD-Gammon's success in 1991, the interest in game-playing agents has risen significantly. With the developments in Deep Learning and emulations for older games have been created, human-level control for Atari games has been achieved and Deep Reinforcement Learning has proven itself to be a success. However, the ancestor of DRL, TD-Gammon, and its game Backgammon got out of sight, because of the fact that Backgammon's actions are much more complex than other games (most of the Atari games has 2 or 4 di...
TDB 1.1: Extensions on Turkish Discourse Bank
Zeyrek Bozşahin, Deniz (2017-4-3)
In this paper we present the recent developments on Turkish Discourse Bank (TDB). We first summarize the resource and present an evaluation. Then, we describe TDB 1.1, i.e. enrichments on 10% of the corpus (namely, added senses for explicit discourse connectives and new annotations for implicit relations, entity relations and alternative lexicalizations). We explain the method of annotation and evaulate the data.
TDB 1.1: Extensions on Turkish Discourse Bank
Zeyrek Bozşahin, Deniz (2017-03-01)
ARC: The analytical rate control scheme for real-time traffic in wireless networks
Akan, OB; Akyildiz, IF (Institute of Electrical and Electronics Engineers (IEEE), 2004-08-01)
Next-generation wireless Internet (NGWI) is expected to provide a wide range of services including real-time multimedia to mobile users. However, the real-time multimedia traffic transport requires rate control deployment to protect shared Internet from unfairness and further congestion collapse. The transmission rate control method must also achieve high throughput and satisfy multimedia requirements such a delay or jitter bound. However, the existing solutions are mostly for the wired Internet, and hence,...
mmm: An R package for analyzing multivariate longitudinal data with multivariate marginal models
Asar, Oezguer; İlk Dağ, Özlem (2013-12-01)
Modeling multivariate longitudinal data has many challenges in terms of both statistical and computational aspects. Statistical challenges occur due to complex dependence structures. Computational challenges are due to the complex algorithms, the use of numerical methods, and potential convergence problems. Therefore, there is a lack of software for such data. This paper introduces an R package mmm prepared for marginal modeling of multivariate longitudinal data. Parameter estimations are achieved by genera...
Citation Formats
M. M. Ankaralı and U. Saranlı, “TD-SLIP: A better predictive model for human running,” presented at the Dynamic Walking 2012, Florida, Amerika Birleşik Devletleri, 2012, Accessed: 00, 2021. [Online]. Available: