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Found 17 papers, 6 papers with code
Tackling Zero Pronoun Resolution and Non-Zero Coreference Resolution Jointly
Zero pronoun resolution aims at recognizing dropped pronouns and pointing out their anaphoric mentions, while non-zero coreference resolution targets at clustering mentions referring to the same entity.
Joint Scattering Environment Sensing and Channel Estimation Based on Non-stationary Markov Random Field
A location domain channel modeling method is proposed based on the position of targets and scatterers in the scattering environment, and the resulting radar and communication channels exhibit a two-dimensional (2-D) joint burst sparsity.
Joint Scattering Environment Sensing and Channel Estimation for Integrated Sensing and Communication
A location domain channel modeling method is proposed based on the position of targets and scatterers in the scattering environment, and the resulting radar and communication channels exhibit a partially common sparsity.
Long-Document Cross-Lingual Summarization
Cross-Lingual Summarization (CLS) aims at generating summaries in one language for the given documents in another language.
Fundamental Limits and Optimization of Multiband Sensing
Then, a metric called the statistical resolution limit (SRL) that provides a resolution limit is employed to investigate the fundamental limits of delay resolution.
A Two-stage Multiband Radar Sensing Scheme via Stochastic Particle-Based Variational Bayesian Inference
To cope with this challenge, we divide the radar target parameter estimation into two stages equipped with different but equivalent signal models, where the first-stage coarse estimation is used to narrow down the search range for the next stage, and the second-stage refined estimation is based on the Bayesian approach to avoid the convergence to a bad local optimum of the likelihood function.
Latency Minimization for mmWave D2D Mobile Edge Computing Systems: Joint Task Allocation and Hybrid Beamforming Design
Mobile edge computing (MEC) and millimeter wave (mmWave) communications are capable of significantly reducing the network's delay and enhancing its capacity.
RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation
Nevertheless, the correlations between knowledge implied in the multi-turn context and the transition regularities between relations in KGs are under-explored.
Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme
In the coarse stage, we exploit the group sparsity structure of the multiband channel and propose a Turbo Bayesian inference (Turbo-BI) algorithm to achieve a good initial delay estimation based on a coarse signal model, which is transformed from the original multiband signal model by absorbing the carrier frequency terms.
Channel Tracking and Prediction for IRS-aided Wireless Communications
Based on the proposed transmission protocol, we propose a two-stage channel tracking and prediction (2SCTP) scheme to obtain the direct and reflected channels with low channel training overhead, which is achieved by exploiting the temporal correlation of the time-varying channels.
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks
Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context.
Knowledge Enhanced Sports Game Summarization
Additionally, we also introduce a knowledge-enhanced summarizer that utilizes both live commentaries and the knowledge to generate sports news.
Successive Convex Approximation Based Off-Policy Optimization for Constrained Reinforcement Learning
We propose a successive convex approximation based off-policy optimization (SCAOPO) algorithm to solve the general constrained reinforcement learning problem, which is formulated as a constrained Markov decision process (CMDP) in the context of average cost.
Two-Stage Stochastic Optimization via Primal-Dual Decomposition and Deep Unrolling
Then we propose a PDD-based stochastic successive convex approximation (PDD-SSCA) algorithmic framework to find KKT solutions for two-stage stochastic optimization problems.
Energy Efficiency Optimization for Millimeter Wave System with Resolution-Adaptive ADCs
This letter investigates the uplink of a multi-user millimeter wave (mmWave) system, where the base station (BS) is equipped with a massive multiple-input multiple-output (MIMO) array and resolution-adaptive analog-to-digital converters (RADCs).
Sparse Bayesian Learning Approach for Discrete Signal Reconstruction
By integrating the discretization enforcing prior into the SBL framework and applying the variational Bayesian inference (VBI) methodology, we devise an alternating optimization algorithm to jointly characterize the finite-alphabet feature and reconstruct the unknown signal.
Stochastic Successive Convex Approximation for Non-Convex Constrained Stochastic Optimization
The proposed CSSCA algorithm can also handle stochastic non-convex constraints in optimization problems, and it opens the way to solving more challenging optimization problems that occur in many applications.
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