Examples of cc.mallet.optimize.OrthantWiseLimitedMemoryBFGS

cc.mallet.optimize.OrthantWiseLimitedMemoryBFGS
Implementation of orthant-wise limited memory quasi Newton method for optimizing convex L1-regularized objectives. See: "Scalable training of l1-regularized log-linear models" by Galen Andrew and Jianfeng Gao in ICML 2007 for details. This code is an adaptation of the freely-available C++ code on Galen's webpage. @author Kedar Bellare

    this.gaussianPriorVariance = Double.MAX_VALUE;
  }


  public Optimizer getOptimizer() {
    if (optimizer == null && optimizable != null)
      optimizer = new OrthantWiseLimitedMemoryBFGS(optimizable, l1Weight);
    return optimizer;
  }

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    if (trainingSet != this.trainingSet || optimizable == null) {
      getOptimizable(trainingSet);
      optimizer = null;
    }
    if (optimizer == null)
      optimizer = new OrthantWiseLimitedMemoryBFGS(optimizable, l1Weight);
    return optimizer;
  }

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  }


  public Optimizer getOptimizer(InstanceList trainingSet) {
    getOptimizableCRF(trainingSet);
    if (opt == null || ocrf != opt.getOptimizable())
      opt = new OrthantWiseLimitedMemoryBFGS(ocrf, l1Weight);
    return opt;
  }

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cc.mallet.classify.MaxEntL1Trainer

cc.mallet.fst.CRFTrainerByL1LabelLikelihood

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