I won the overall contest and also all the 4 city level prizes on the SpaceNet Challenge Round 2. This blogpost describes my winning solution on the public challenge hosted by Topcoder Marathon Match. Summary¶ Adding OpenStreetMap layers into the input of U-Net model significantly improves F-score. For training a deep neural network model, the computational time on p2.xlarge (Tesla K80) is two tim
2. 発表の構成 機械学習のデータ並列処理 • 勾配降下法の基礎 • Distributed Gradient • Tree Reduce • AllReduce • Parameter Mixing • Parameter Server • Mix Server 2 4. 1. Distributed Gradient (Gradient Averaging) • 勾配計算の並列化 • 重みの更新は基本的に単一ノード • モデルは共有しない 2. Parameter Mixing (Model Averaging) • 確率的勾配降下法の学習処理を並列化 • 重みの更新が各学習器の計算ノードで行われ,その後 モデルの平均化処理が行われる • モデルを共有する 機械学習のデータ並列処理 機械学習のデータ並列処理手法は 基本的にこの2種類かその亜種に分類できる 4 5. 機械学習の分散処理の
(We have also published the translated versions of this blog post in Deutsche, עִברִית, Italiano, 日本語, 한국어, русский and Español ) Definitions UASF: User Activated Soft Fork. Developers add a mandatory rule set to change the node’ software, invalidating certain kinds of previously valid blocks after a flag day. This method requires no mining majority to support or activate a chain-split. The UASF p
Latest news Discover our latest AI breakthroughs and updates from the lab Responsibility & Safety The ethics of advanced AI assistants The ethics of advanced AI assistants Exploring the promise and risks of a future with more capable AI Research TacticAI: an AI assistant for football tactics As part of our multi-year collaboration with Liverpool FC, we develop a full AI system that can advise coac
We present a new probabilistic model of compact commutative Lie groups that produces invariant-equivariant and disentangled representations of data. To define the notion of disentangling, we borrow a fundamental principle from physics that is used to derive the elementary particles of a system from its symmetries. Our model employs a newfound Bayesian conjugacy relation that enables fully tractabl
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