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Found 12 papers, 1 papers with code
Channel Measurements and Modeling for Dynamic Vehicular ISAC Scenarios at 28 GHz
Integrated sensing and communication (ISAC) is a promising technology for 6G, with the goal of providing end-to-end information processing and inherent perception capabilities for future communication systems.
Characterization of Wireless Channel Semantics: A New Paradigm
Recently, deep learning enabled semantic communications have been developed to understand transmission content from semantic level, which realize effective and accurate information transfer.
Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz
It is necessary to carry out measurement, characterization, and modeling for vehicular ISAC channels as the basic theoretical support for system design.
A Cluster-Based Statistical Channel Model for Integrated Sensing and Communication Channels
However, some important features of ISAC channels have not been well characterized, for example, most existing ISAC channel models consider communication channels and sensing channels independently, whereas ignoring correlation under the consistent environment.
Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking
In order to pass better ads from the early to the final stage ranking, we propose a multi-task learning framework for early stage ranking to capture multiple final stage ranking components (i. e. ads clicks and ads quality events) and their task relations.
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations
However, MTL research faces two challenges: 1) effectively modeling the relationships between tasks to enable knowledge sharing, and 2) jointly learning task-specific and shared knowledge.
P$^2$SDF for Neural Indoor Scene Reconstruction
As the unsupervised plane segments are usually noisy and inaccurate, we propose to assign different weights to the sampled points on the plane in plane estimation as well as the regularization loss.
A Class-wise Non-salient Region Generalized Framework for Video Semantic Segmentation
In this paper, we propose a class-wise non-salient region generalized (CNSG) framework for the VGSS task.
Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives
One contribution of this paper is that we establish some close relationships between the \textit{outcome conditioned average partial effects} and a class of parameters measuring the effect of counterfactually changing the distribution of a single covariate on the unconditional outcome quantiles.
Guaranteed Fixed-Confidence Best Arm Identification in Multi-Armed Bandits: Simple Sequential Elimination Algorithms
We propose to use the classical "vector at a time" (VT) rule, which samples each remaining arm once in each round.
Joint COCO and Mapillary Workshop at ICCV 2019 Keypoint Detection Challenge Track Technical Report: Distribution-Aware Coordinate Representation for Human Pose Estimation
Taking them together, we formulate a novel Distribution-Aware coordinate Representation for Keypoint (DARK) method.
An efficient quantum algorithm for generative machine learning
A central task in the field of quantum computing is to find applications where quantum computer could provide exponential speedup over any classical computer.
