Lecture 15 | Efficient Methods and Hardware for Deep Learning
In Lecture 15, guest lecturer Song Han discusses algorithms and specialized hardware that can be used to accelerate training and inference of deep learning workloads. We discuss pruning, weight sharing, quantization, and other techniques for accelerating inference, as well as parallelization, mixed precision, and other techniques for accelerating training. We discuss specialized hardware for deep
Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning
In order for robots to perform mission-critical tasks, it is essential that they are able to quickly adapt to changes in their environment as well as to injuries and or other bodily changes. Deep reinforcement learning has been shown to be successful in training robot control policies for operation in complex environments. However, existing methods typically employ only a single policy. This can l
Deep Learning - The Straight Dope — The Straight Dope 0.1 documentation
Crash course Preface Introduction Manipulate data the MXNet way with ndarray Linear algebra Intermediate linear algebra Probability and statistics Automatic differentiation with autograd Introduction to supervised learning Linear regression from scratch Linear regression with gluon Binary classification with logistic regression Multiclass logistic regression from scratch Multiclass logistic regres
Generalization in Deep Learning
This paper provides theoretical insights into why and how deep learning can generalize well, despite its large capacity, complexity, possible algorithmic instability, nonrobustness, and sharp minima, responding to an open question in the literature. We also discuss approaches to provide non-vacuous generalization guarantees for deep learning. Based on theoretical observations, we propose new open
Rainbow: Combining Improvements in Deep Reinforcement Learning
The deep reinforcement learning community has made several independent improvements to the DQN algorithm. However, it is unclear which of these extensions are complementary and can be fruitfully combined. This paper examines six extensions to the DQN algorithm and empirically studies their combination. Our experiments show that the combination provides state-of-the-art performance on the Atari 260
Tensorflow Text Classification - Python Deep Learning - Source Dexter
What is Tensorflow Text Classification all About? Text Classification is the task of assigning the right label to a given piece of text. This text can either be a phrase, a sentence or even a paragraph. Our aim would be to take in some text as input and attach or assign a label to it. Since we will be using Tensor Flow Is deep learning library, we can call this the Tensorflow text classification s
Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations
The recent breakthroughs of deep reinforcement learning (DRL) technique in Alpha Go and playing Atari have set a good example in handling large state and actions spaces of complicated control problems. The DRL technique is comprised of (i) an offline deep neural network (DNN) construction phase, which derives the correlation between each state-action pair of the system and its value function, and
スライド上でコードが動く！Jupyter+RISEによるプレゼン環境 | Code Craft House
Jupyter のノートブックでプレゼンするための拡張機能、 RISE を試してみたので、環境構築や使い方についてまとめてみました。今回紹介する方法では、静的なHTMLに変換するのではなく 実行中のJupyterノートをプレゼン形式で見せる ことが可能で、 プレゼン表示のままコードの実行もできてしまう スゴイやつです。そのうち発表するときに使ってみたいなあと思いながら、自分用のメモを兼ねて一通り動かすところまで記事にしてみます。 RISEについて RISEは、実行中のJupter Notebookをスライド表示するための拡張機能になります。実行中の、というのがミソで、コードサンプルをスライドに載せるだけではなく、 スライド上のコードを書き換えたり、そのまま再実行する ことが可能になります。うたい文句にも "Live" という文字があるのですが、入力値をその場で書き換えて挙動の変化を見せるよ
Video Generation From Text
Generating videos from text has proven to be a significant challenge for existing generative models. We tackle this problem by training a conditional generative model to extract both static and dynamic information from text. This is manifested in a hybrid framework, employing a Variational Autoencoder (VAE) and a Generative Adversarial Network (GAN). The static features, called "gist," are used to
Deep RL Bootcamp - Lectures
Core Lecture 1 Intro to MDPs and Exact Solution Methods -- Pieter Abbeel (video | slides) Core Lecture 2 Sample-based Approximations and Fitted Learning -- Rocky Duan (video | slides) Core Lecture 3 DQN + Variants -- Vlad Mnih (video | slides) Core Lecture 4a Policy Gradients and Actor Critic -- Pieter Abbeel (video | slides) Core Lecture 4b Pong from Pixels -- Andrej Karpathy (video | slides) Cor
Deep RL Bootcamp - Labs
Prelab instructions: Set up your computer for all labs. Lab 1: Markov Decision Processes. You will implement value iteration, policy iteration, and tabular Q-learning and apply these algorithms to simple environments including tabular maze navigation (FrozenLake) and controlling a simple crawler robot. Lab 2: Introduction to Chainer. You will implement deep supervised learning using Chainer, and a
Unitogel: Link Alternatif Unitogel Terbaru 2025 Dan Akses Login Unitogel Paling Gampang
Unitogel: Link Alternatif Unitogel Terbaru 2025 Dan Akses Login Unitogel Paling Gampang Dalam dunia togel online yang semakin berkembang, memilih platform yang tepat sangat penting untuk kenyamanan dan keamanan bermain. Salah satu nama yang sudah tidak asing lagi di kalangan penggemar togel adalah bandar Unitogel. Dikenal sebagai bandar Unitogel terpercaya dan profesional, Unitogel menawarkan berb
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AWS Deep Learning AMI Now Supports PyTorch, Keras 2 and Latest Deep Learning Frameworks
Nao Tokui / 徳井直生 on Twitter: "Googleの担当するJeff Dean氏のトーク. 以前は50万行以上あったGoogle翻訳のソースコードが、Deep Learning導入によって約500行にまで削減でできたらしい. https://t.co/I9xstDsPCL"
New Optimizations Improve Deep Learning Frameworks For CPUs
GPUでディープラーニングやるならAWSよりFloydHub - Qiita
NVIDIA、現行品の約13倍の性能を持つ「DRIVE PX PEGASUS」をドイツで発表。レベル5自動運転が実現可能に
GitHub - salesforce/pytorch-qrnn: PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM
20年の歴史を持つ囲碁ソフト「銀星囲碁」が八段免状取得試験に挑戦 〜本日10時から／市販のPCや囲碁ソフトが八段免状の取得に挑戦するのは世界で初めての試み
IBM Maximo Visual Inspection