• DnCNN

  • Referenced in 30 articles [sw39678]
  • blind Gaussian denoising). With the residual learning strategy, DnCNN implicitly removes the latent clean image...
  • Pueblo

  • Referenced in 30 articles [sw00743]
  • light-weight and efficient hybrid learning and backjumping strategy for analyzing PB constraints...
  • DistAl

  • Referenced in 101 articles [sw01746]
  • constructive learning algorithms that use an iterative (and often time consuming) weight modification strategy ... demonstrate that DistAl compares favorably with other learning algorithms for pattern classification...
  • DISCOUNT

  • Referenced in 14 articles [sw19613]
  • distributed and learning equational prover DISCOUNT. The DISCOUNT system is a distributed equational theorem prover ... quantified goals. DISCOUNT features many different control strategies that cooperate using the teamwork approach. Competition ... control strategies based on learning from previous proof experiences. One of these strategies forms...
  • E-MaLeS

  • Referenced in 11 articles [sw15190]
  • MaLeS 1.1. Picking the right search strategy is important for the success of automatic theorem ... meta-system that uses machine learning and strategy scheduling to optimize the performance ... kernel-based learning method to predict the run-time of a strategy on a given...
  • AWESOME

  • Referenced in 14 articles [sw40128]
  • multiagent learning algorithm are that it (1). learns to play optimally against stationary opponents ... games-assuming that the opponent’s mixed strategy is observable. Another algorithm, ReDVaLeR (which ... actual actions ((not) their mixed strategies). It also learns to play optimally against opponents that ... adapt to the others’ strategies when they appear stationary, but otherwise to retreat...
  • CMA-ES

  • Referenced in 116 articles [sw05063]
  • values are generated. In an evolution strategy, new candidate solutions are sampled according ... Adaptation of the covariance matrix amounts to learning a second order model of the underlying...
  • CORN

  • Referenced in 6 articles [sw15436]
  • trade algorithm termed CORrelation-driven Nonparametric learning strategy (CORN) for actively trading stocks. CORN effectively ... between stock market windows via a nonparametric learning approach. We evaluate the empirical performance...
  • HySAT

  • Referenced in 25 articles [sw01980]
  • isomorphic replication of learned conflict clauses or tailored decision strategies, and extends them...
  • iDHS-EL

  • Referenced in 10 articles [sw22426]
  • pseudo nucleotide composition into an ensemble learning framework. MOTIVATION: Regulatory DNA elements are associated with ... this study, using the strategy of ensemble learning framework, we proposed a new predictor called...
  • ISETL

  • Referenced in 20 articles [sw01370]
  • theory of learning. Examples are given of uses of this pedagogical strategy in abstract algebra...
  • MINDFUL

  • Referenced in 4 articles [sw08865]
  • INDuctive neuro-FUzzy Learning. Common inductive learning strategies offer tools for knowledge acquisition, but possess ... fixed bias during the learning process. To overcome the limitations of such base-learning approaches...
  • ProDiGe

  • Referenced in 3 articles [sw12407]
  • Genes. ProDiGe implements a novel machine learning strategy based on learning from positive and unlabeled...
  • libact

  • Referenced in 3 articles [sw21839]
  • only implements several popular active learning strategies, but also features the active-learning-by-learning...
  • utiml

  • Referenced in 3 articles [sw27783]
  • Multi-Label Learning. Multi-label learning strategies and others procedures to support multi- label classification...
  • PAMR

  • Referenced in 10 articles [sw15437]
  • article proposes a novel online portfolio selection strategy named “Passive Aggressive Mean Reversion” (PAMR). Unlike ... learning technique from machine learning, the proposed portfolio selection strategy can effectively exploit the mean...
  • ELF

  • Referenced in 4 articles [sw26533]
  • Flexible Research Platform for Real-time Strategy Games. In this paper, we propose ... reinforcement learning research. Using ELF, we implement a highly customizable real-time strategy (RTS) engine ... notebook. When coupled with modern reinforcement learning methods, the system can train a full-game ... game replays, we show our agents learn interesting strategies. ELF, along with its RL platform...
  • iCaRL

  • Referenced in 5 articles [sw37989]
  • development of incrementally learning systems that learn about more and more concepts over time from ... introduce a new training strategy, iCaRL, that allows learning in such a class-incremental ... learn many classes incrementally over a long period of time where other strategies quickly fail...
  • ExSTraCS

  • Referenced in 2 articles [sw28621]
  • major concern for any machine learning strategy in this age of ‘big data’. A large ... introduced as an extended Michigan-style supervised learning classifier system that combined ... heterogeneous problem domains. While Michigan-style learning classifier systems are powerful and flexible learners, they ... algorithm and introduces an effective strategy to dramatically improve learning classifier system scalability. ExSTraCS...
  • FANT

  • Referenced in 11 articles [sw10091]
  • number of search strategies such as intensification, diversification and learning mechanisms. FANT is used...