Experimental results revealed that our framework healed the truncation bias occurred in previous work and outperformed state-of-the-art methods while ...

We develop an extensional truncation framework to Dual Averaging, which retains rarely occurring but informative features. Our proposed framework integrates ...

This work develops an extensional truncation framework to Dual Averaging, which retains rarely occurring but informative features and outperforms other ...

In addition, our framework achieves the same computational complexity and regret bound as standard Dual Averaging. Experiments demonstrated that our framework ...

Hidekazu Oiwa, Shin Matsushima, Hiroshi Nakagawa: Healing Truncation Bias: Self-Weighted Truncation Framework for Dual Averaging. ICDM 2012: 575-584.

Healing truncation bias: self-weighted truncation framework for dual averaging. H Oiwa, S Matsushima, H Nakagawa. 2012 IEEE 12th International Conference on ...

Healing Truncation Bias: Self-weighted Truncation Framework for Dual Averaging. H Oiwa, S Matsushima, H Nakagawa. Data Mining (ICDM), 2012 IEEE 12th ...

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Apr 25, 2024 · Healing Truncation Bias: Self-Weighted Truncation Framework for Dual Averaging. ICDM 2012: 575-584; 2011. [c1]. view. electronic edition via DOI ...

Publications. Publications (2). Healing Truncation Bias: Self-Weighted Truncation Framework for Dual Averaging. Conference Paper. Dec 2012.