LIP6

Sharper Bounds on the Required Fixed-Point Precision for Emulating Floating-Point Matrix Multiplication

Precision emulation algorithms, such as the Ozaki schemes, can leverage low-precision matrix multiply–accumulate to approximate the product \(AB\) , where \(A\) and \(B\) are high-precision floating-point matrices, via fixed-point arithmetic. A key difficulty of these approaches...

Sampled-Based Guided Quantum Walk: Non-variational quantum algorithm for combinatorial optimization

We introduce SamBa-GQW, a novel quantum algorithm for solving binary combinatorial optimization problems of arbitrary degree with no use of any classical optimizer. The algorithm is based on a continuous-time quantum walk on the solution space represented as a graph. The walker e...

Error-Controlled Mixed-Precision Cholesky Factorization with MX Microscaling Formats

Existing tile-centric mixed-precision Cholesky factorization, as used in recent Gordon Bell campaigns, is based on a heuristic that bounds only rounding contribution while ignoring underflow when classifying tiles for different IEEE floating point precisions. Direct application t...

Hoeffding adaptive splitting trees for data stream classification with concept drift and ensemble learning

Abstract Ensembles of decision trees are well-established methods for data stream classification. In ensemble learning, Hoeffding Trees are widely adopted as base learners, performing periodic split attempts according to the Hoeffding bound. Recent studies, however, indicate that...