Quicker ADC : Unlocking the Hidden Potential of Product Quantization With SIMD.

Efficient Nearest Neighbor (NN) search in high-dimensional spaces is a foundation of many multimedia retrieval systems. A common approach is to rely on Product Quantization, which allows the storage of large vector databases in memory and efficient distance computations. Yet, implementations of nearest neighbor search with Product Quantization have their performance limited by the many memory accesses they perform.

Towards a personalized Internet: a case for a full decentralization.

The Web has become a user-centric platform where users post, share, annotate, comment and forward content be it text, videos, pictures, URLs, etc. This social dimension creates tremendous new opportunities for information exchange over the Internet, as exemplified by the surprising and exponential growth of social networks and collaborative platforms. Yet, niche content is sometimes difficult to retrieve using traditional search engines because they target the mass rather than the individual.