Today's Internet Services are undergoing fundamental changes and shifting to an intelligent
computing era where AI is widely employed to augment services. In this context, many …

AI benchmarking provides yardsticks for benchmarking, measuring and evaluating
innovative AI algorithms, architecture, and systems. Coordinated by BenchCouncil, this …

Modern real-world application scenarios like Internet services consist of a diversity of AI and
non-AI modules with huge code sizes and long and complicated execution paths, which …

Earlier-stage evaluations of a new AI architecture/system need affordable AI benchmarks.
Only using a few AI component benchmarks like MLPerf alone in the other stages may lead …

In recent years, with the trend of applying deep learning (DL) in high performance scientific
computing, the unique characteristics of emerging DL workloads in HPC raise great …

Learning-to-rank (LTR) has become a key technology in E-commerce applications. Most
existing LTR approaches follow a supervised learning paradigm with data collected from an …

Learning effective feature crosses is the key behind building recommender systems.
However, the sparse and large feature space requires exhaustive search to identify effective …

Artificial Intelligence (AI) is now the center of attention for many industries, ranging from
private companies to academic institutions. While domains of interest and AI applications …

As research and practice in artificial intelligence (AI) grow in leaps and bounds, the
resources necessary to sustain and support their operations also grow at an increasing …

Despite the development of ranking optimization techniques, pointwise loss remains the
dominating approach for click-through rate prediction. It can be attributed to the calibration …