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Found 8 papers, 2 papers with code
Neural Implicit Field Editing Considering Object-environment Interaction
To obtain illuminating conditions from the mixture soup, the system successfully separates the interaction between objects and scene environment by intrinsic decomposition method.
LFG: A Generative Network for Real-Time Recommendation
The recommendation model known as LFM (Latent Factor Model), which captures latent features through matrix factorization and gradient descent to fit user preferences, has given rise to various recommendation algorithms that bring new improvements in recommendation accuracy.
TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for Inference Cost Reduction
Our summarization compression can reduce 65% of the retrieval token size with further 0. 3% improvement on the accuracy; semantic compression provides a more flexible way to trade-off the token size with performance, for which we can reduce the token size by 20% with only 1. 6% of accuracy drop.
ARAI-MVSNet: A multi-view stereo depth estimation network with adaptive depth range and depth interval
Moreover, our method also achieves the lowest $e_{1}$ and $e_{3}$ on the BlendedMVS dataset and the highest Acc and $F_{1}$-score on the ETH 3D dataset, surpassing all listed methods. Project website: https://github. com/zs670980918/ARAI-MVSNet
Data-driven Piecewise Affine Decision Rules for Stochastic Programming with Covariate Information
Focusing on stochastic programming (SP) with covariate information, this paper proposes an empirical risk minimization (ERM) method embedded within a nonconvex piecewise affine decision rule (PADR), which aims to learn the direct mapping from features to optimal decisions.
CPS Attack Detection under Limited Local Information in Cyber Security: A Multi-node Multi-class Classification Ensemble Approach
In order to train a global multi-class classifier without sharing the raw data across all nodes, the main result of our study is designing a multi-node multi-class classification ensemble approach.
Automatic Generation of Multi-precision Multi-arithmetic CNN Accelerators for FPGAs
Furthermore, we show how Tomato produces implementations of networks with various sizes running on single or multiple FPGAs.
Equivalence Checking of Quantum Finite-State Machines
In this paper, we introduce the model of quantum Mealy machines and study the equivalence checking and minimisation problems of them.
Formal Languages and Automata Theory Quantum Physics
