conferences

Word Mover’s Embedding: Universal Text Embedding from Word2Vec

Text representation plays an important role in many natural language processing (NLP) tasks such as document classification and clustering, sense disambiguation, machine translation, and document matching. Since there are no explicit features in text, developing effective text representations is an important goal in AI and NLP research. A fundamental challenge in this respect is learning […]

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Sensemaker Series: IBM Researchers on Future Tech for Financial Services

The financial services industry faces mounting pressures to reduce costs, improve customer experience, compete with emerging players, and comply with new regulations. At the same time, IBM Research is driving innovations that will transform the financial services industries using technologies like AI, blockchain, quantum computing, IoT, cybersecurity, and cloud. These advances are surfacing new capabilities […]

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Helping to Improve Medical Image Analysis with Deep Learning

Medical imaging creates tremendous amounts of data: many emergency room radiologists must examine as many as 200 cases each day, and some medical studies contain up to 3,000 images. Each patient’s image collection can contain 250GB of data, ultimately creating collections across organizations that are petabytes in size. Within IBM Research, we see potential in […]

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Using AI to Design Deep Learning Architectures

Selecting the best architecture for deep learning architectures is typically a time-consuming process that requires expert input, but using AI can streamline this process. I am developing an evolutionary algorithm for architecture selection that is up to 50,000 times faster than other methods, with only a small increase in error rate. Deep learning models are […]

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An End-to-End Approach for Scaling Up Spectral Clustering

Clustering is one of the most fundamental problems in machine learning and data mining tasks, such as image segmentation, power load clustering, and community detection for social networks. But well-known clustering techniques like K-Means, which is based on Euclidean proximity, may not be capable of clustering data that lies on a high-dimensional manifold, as illustrated […]

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Corpus Conversion Service Makes PDF Content Discoverable

This week, my team from IBM Research will debut a massively scalable document ingestion system, the Corpus Conversion Service, at the prestigious ACM Conference on Knowledge Discovery and Data Mining (KDD 2018) in London. Our AI-based cloud system can ingest 100,000 PDF pages per day (even of scanned documents) on a single blade server with […]

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FEED 2018: Applying Data Analytics to Earth and Environmental Science

The workshop Fragile Earth: Theory Guided Data Science to Enhance Scientific Discovery (FEED 2018) will take place August 20, as part of the Knowledge Discovery and Data mining conference (KDD 2018) in London. The FEED 2018 co-chairs and -organizers all welcome you to join us! FEED 2018 will bring together the research, industry, and policy […]

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Advancing Knowledge Discovery at KDD 2018

The annual Association for Computing Machinery (ACM) Knowledge Discovery and Data mining conference (KDD 2018) takes place August 19–23, 2018, in London, UK. The interdisciplinary conference brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data with two tracks: Research Track and Applied Data Science Track. IBM […]

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Improving AI’s Language Skills at ACL 2018

The 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018) will be held July 15–20 in Melbourne, Australia. ACL received 1,544 submissions and accepted 384, for an overall acceptance rate of 24.9 percent. IBM Research AI will present multiple papers at ACL 2018 and is proud to be a Gold sponsor. Please plan […]

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