4 citations · 7 across the 11 of their papers we have counts for
11 papers
Binary Quantized Neural Network Training Is W[1]-Hard Parameterized by Input and Output Dimensions
Tao Jiang, Minbo Gao, Shaowei Cai
Ganian et al. (ICLR 2026) proved that quantized neural network training is fixed-parameter tractable when parameterized jointly by architecture treewidth, input dimension , and…
The Exact Approximation Ratio of the Optimal Fixed-Price Mechanism in Bilateral Trade
Tao Jiang, Minbo Gao, Shaowei Cai
In bilateral trade, a seller owns an item that a buyer may value more, and their values are drawn independently from known distributions. A fixed-price mechanism posts a single pri…
Exact Minimax One-Bit Unbiased Compression: Heavy-Tail Necessity and Finite-Randomness Approximation
Tao Jiang, Minbo Gao, Shaowei Cai
A pointwise-unbiased one-bit compressor reconstructs every real input in expectation while transmitting one bit. For a scalar source with CDF , mean , and $\mathcal J(P)=…
Depth Enables Local Entropy: Quadratic Depth Dependence in Deep Variation-Norm ReLU Regression
Tao Jiang, Minbo Gao, Shaowei Cai
We study Gaussian regression over the explicit vector-valued Parhi--Nowak deep-RBV^2 architecture with depth L, width w, layer-sum variation budget A, and output bound B. For this…
Polynomial-Time Singular Witnesses for Non-SNS Sign Patterns
Tao Jiang, Minbo Gao, Shaowei Cai
Sign-nonsingularity asks whether every real matrix with prescribed entry signs is nonsingular. Polynomial-time algorithms recognize square sign-nonsingular patterns through their c…
A Better Analysis For PPSZ For 3-SAT
Tao Jiang, Shaowei Cai
The PPSZ algorithm of Paturi, Pudlák, Saks, and Zane solves 3-SAT by processing the variables in a uniformly random order, setting a variable whenever a bounded number of clauses i…
EvoGM: Learning to Merge LLMs via Evolutionary Generative Optimization
Tao Jiang, Xinmeng Yu, Chenhao Yi +5
Evolutionary model merging provides a powerful framework for the automated, training-free composition of LLMs through parameter-space search. However, existing methods predominantl…
Beyond Speedups: Hardware-Aware Evaluation of Evolutionary Algorithms on GPUs
Xinmeng Yu, Tao Jiang, Ran Cheng +2
Evolutionary algorithms (EAs) are increasingly executed on graphics processing units (GPUs) to exploit population-level parallelism. This shift changes the resource model under whi…
Evolutionary Generative Optimization: Towards Fully Data-Driven Evolutionary Optimization via Generative Learning
Tao Jiang, Kebin Sun, Zhenyu Liang +3
Recent advances in data-driven evolutionary algorithms (EAs) have demonstrated the potential of leveraging historical data to improve optimization accuracy and adaptability. Despit…
Tensorized Ant Colony Optimization for GPU Acceleration
Luming Yang, Tao Jiang, Ran Cheng
Ant Colony Optimization (ACO) is renowned for its effectiveness in solving Traveling Salesman Problems, yet it faces computational challenges in CPU-based environments, particularl…
GPU-accelerated Evolutionary Multiobjective Optimization Using Tensorized RVEA
Zhenyu Liang, Tao Jiang, Kebin Sun +1
Evolutionary multiobjective optimization has witnessed remarkable progress during the past decades. However, existing algorithms often encounter computational challenges in large-s…