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KDD 2018, the 24th ACM Conference on Knowledge Discovery and Data Mining took place in London, United Kingdom on August 19-23 in the heart of London’s historic Royal Docks.

In addition to an astonishing program featuring peer-reviewed papers, workshops, hands-on tutorials, deep learning day and Health Day – an entire day dedicated to discussing machine learning trends and addressing challenges in healthcare, attendees were treated to outstanding keynote talks by Imperial College London Emeritus Professor of Mathematics David Hand, Nobel Laureate Alvin Roth, Columbia University’s Data Science Director Jeannette Wing and Oxford University Professor Yee Whye Teh.

Joseph Sirosh, Corporate Vice President and CTO for AI gave a well-attended invited talk titled, “Planet-scale Land Cover Classification with FPGAs” in which he demonstrated the power of Azure Machine Learning and Project Brainwave in classification of terabytes of land cover aerial images using DNNs and tackling use cases such as wildlife poacher recognition.

Data Preprocessing

Project Name: Learning by Doing (LBD) based course content development Project Investigator: Prof Sandhya Kode.

Building Explainable Machine Learning Systems: The Good, the Bad, and the Ugly

This meetup was held in New York City on 30th April. Abstract: The good news is building fair, accountable, and transparent machine learning systems is ...

Big Data in Climate: Opportunities and Challenges for Machine Learning

Author: Vipin Kumar, Department of Computer Science and Engineering, University of Minnesota Abstract: This talk will present an overview of research being ...

Temporal Learning in Video Data Using Deep Learning and Gaussian Processes

Author: Abhishek Srivastav, General Electric Company Abstract: This paper presents an approach for data-driven modeling of hidden, stationary temporal ...

Machine Learning Best Algorithms: Gradient Boosting Machines (GBM) July 19, 2018

Machine Learning Best Algorithms: Gradient Boosting Machines (GBM) Szilard Pafka: July 19, 2018 Hosted by Szilard Pafka From LA Big Data Science, Deep ...

Exploiting the Computation Graph for Large Scale Distributed Machine Learning

Author: S.V.N. Vishwanathan, Department of Computer Science, University of California Santa Cruz Abstract: Many machine learning algorithms minimize a ...

On-Device Machine Intelligence with Neural Projections

Deep neural networks and other machine learning models have been transformative for building intelligent systems capable of visual recognition, speech and ...

DEF CON 22 - Secure Because Math - A Deep Dive On Machine Learning - Based Monitoring

DEF CON 22 Hacking Conference Presentation By Alex Pinto Secure Because Math - A Deep Dive On Machine Learning - Based Monitoring.

KDD2016 paper 567

Title: Graph Wavelets via Sparse Cuts Authors: Arlei Lopes da Silva*, University of California, Santa Barbara Xuan-Hong Dang, University of California, Santa ...

Prabhakar's Keynote: Reinventing Productivity Using AI

Prabhakar Raghavan, VP of Apps at Google Cloud talks about Reinventing productivity using AI at the AI/ML Workshop on research and practice in India.