Search Results for author: Xin Qiu

Found 8 papers, 6 papers with code

BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed Cluster

1 code implementation3 Apr 2022 Jason Dai, Ding Ding, Dongjie Shi, Shengsheng Huang, Jiao Wang, Xin Qiu, Kai Huang, Guoqiong Song, Yang Wang, Qiyuan Gong, Jiaming Song, Shan Yu, Le Zheng, Yina Chen, Junwei Deng, Ge Song

To address this challenge, we have open sourced BigDL 2. 0 at https://github. com/intel-analytics/BigDL/ under Apache 2. 0 license (combining the original BigDL and Analytics Zoo projects); using BigDL 2. 0, users can simply build conventional Python notebooks on their laptops (with possible AutoML support), which can then be transparently accelerated on a single node (with up-to 9. 6x speedup in our experiments), and seamlessly scaled out to a large cluster (across several hundreds servers in real-world use cases).

AutoML Distributed Computing +1

Simple Genetic Operators are Universal Approximators of Probability Distributions (and other Advantages of Expressive Encodings)

no code implementations19 Feb 2022 Elliot Meyerson, Xin Qiu, Risto Miikkulainen

The conclusion is that, across evolutionary computation areas as diverse as genetic programming, neuroevolution, genetic algorithms, and theory, expressive encodings can be a key to understanding and realizing the full power of evolution.

Detecting Misclassification Errors in Neural Networks with a Gaussian Process Model

1 code implementation5 Oct 2020 Xin Qiu, Risto Miikkulainen

This framework, RED, builds an error detector on top of the base classifier and estimates uncertainty of the detection scores using Gaussian Processes.

Gaussian Processes

From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic

1 code implementation28 May 2020 Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu, Elisa Canzani, Babak Hodjat

Several models have been developed to predict how the COVID-19 pandemic spreads, and how it could be contained with non-pharmaceutical interventions (NPIs) such as social distancing restrictions and school and business closures.

Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel

2 code implementations ICLR 2020 Xin Qiu, Elliot Meyerson, Risto Miikkulainen

In many such tasks, the point prediction is not enough: the uncertainty (i. e. risk or confidence) of that prediction must also be estimated.

BigDL: A Distributed Deep Learning Framework for Big Data

2 code implementations16 Apr 2018 Jason Dai, Yiheng Wang, Xin Qiu, Ding Ding, Yao Zhang, Yanzhang Wang, Xianyan Jia, Cherry Zhang, Yan Wan, Zhichao Li, Jiao Wang, Shengsheng Huang, Zhongyuan Wu, Yang Wang, Yuhao Yang, Bowen She, Dongjie Shi, Qi Lu, Kai Huang, Guoqiong Song

This paper presents BigDL (a distributed deep learning framework for Apache Spark), which has been used by a variety of users in the industry for building deep learning applications on production big data platforms.

Fraud Detection Object Detection

Enhancing Evolutionary Conversion Rate Optimization via Multi-armed Bandit Algorithms

no code implementations10 Mar 2018 Xin Qiu, Risto Miikkulainen

Traffic is allocated to candidate solutions using a multi-armed bandit algorithm, using more traffic on those evaluations that are most useful.

Cannot find the paper you are looking for? You can Submit a new open access paper.