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Found 24 papers, 5 papers with code
Efficient Dialogue Complementary Policy Learning via Deep Q-network Policy and Episodic Memory Policy
Most of the existing dialogue policy methods rely on a single learning system, while the human brain has two specialized learning and memory systems, supporting to find good solutions without requiring copious examples.
Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning
Automatic speaker verification systems are vulnerable to a variety of access threats, prompting research into the formulation of effective spoofing detection systems to act as a gate to filter out such spoofing attacks.
Multi-source Domain Adaptation for Text-independent Forensic Speaker Recognition
A comprehensive set of experiments are conducted to demonstrate that: 1) diverse acoustic environments do impact speaker recognition performance, which could advance research in audio forensics, 2) domain adversarial training learns the discriminative features which are also invariant to shifts between domains, 3) discrepancy-minimizing adaptation achieves effective performance simultaneously across multiple acoustic domains, and 4) moment-matching adaptation along with dynamic distribution alignment also significantly promotes speaker recognition performance on each domain, especially for the LENA-field domain with noise compared to all other systems.
VTC-LFC: Vision Transformer Compression with Low-Frequency Components
Although Vision transformers (ViTs) have recently dominated many vision tasks, deploying ViT models on resource-limited devices remains a challenging problem.
Hybrid Physical Metric For 6-DoF Grasp Pose Detection
6-DoF grasp pose detection of multi-grasp and multi-object is a challenge task in the field of intelligent robot.
A collaborative decomposition-based evolutionary algorithm integrating normal and penalty-based boundary intersection for many-objective optimization
On the other hand, the parallel reference lines of the parallel decomposition methods including the normal boundary intersection (NBI) might result in poor diversity because of under-sampling near the boundaries for MaOPs with concave frontiers.
Noisy Boundaries: Lemon or Lemonade for Semi-supervised Instance Segmentation?
We construct a framework for semi-supervised instance segmentation by assigning pixel-level pseudo labels.
Impact of Naturalistic Field Acoustic Environments on Forensic Text-independent Speaker Verification System
Audio analysis for forensic speaker verification offers unique challenges in system performance due in part to data collected in naturalistic field acoustic environments where location/scenario uncertainty is common in the forensic data collection process.
Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation
Depth estimation is solved as a regression or classification problem in existing learning-based multi-view stereo methods.
Ranked #3 on
3D Reconstruction
on DTU
Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification
To combat the noisy labeling, we propose noise-resistant semi-supervised learning by quantifying the region uncertainty.
Consensus-Based Decentralized Energy Trading for Distributed Energy Resources
In smart grids, distributed energy resources (DERs) have penetrated residential zones to provide a new form of electricity supply, mainly from renewable energy.
Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection
In this paper, we delve into semi-supervised object detection where unlabeled images are leveraged to break through the upper bound of fully-supervised object detection models.
Three-dimensional charge density wave and robust zero-bias conductance peak inside the superconducting vortex core of a kagome superconductor CsV$_3$Sb$_5$
The transition-metal-based kagome metals provide a versatile platform for correlated topological phases hosting various electronic instabilities.
Superconductivity Strongly Correlated Electrons
Magnonic frequency comb through nonlinear magnon-skyrmion scattering
An optical frequency comb consists of a set of discrete and equally spaced frequencies and has found wide applications in the synthesis over broad spectral frequencies of electromagnetic wave and precise optical frequency metrology.
Mesoscale and Nanoscale Physics Optics
Automatic Curriculum Learning With Over-repetition Penalty for Dialogue Policy Learning
We propose a novel framework, Automatic Curriculum Learning-based Deep Q-Network (ACL-DQN), which replaces the traditional random sampling method with a teacher policy model to realize the dialogue policy for automatic curriculum learning.
Geometric Electrostatic Particle-In-Cell Algorithm on Unstructured Meshes
We compare the energy conservation property of the geometric PIC algorithm derived from the discrete variational principle with that of previous PIC methods on unstructured meshes.
Plasma Physics
Spin-wave focusing induced skyrmion generation
We propose a new method to generate magnetic skyrmions through spin-wave focusing in chiral ferromagnets. A lens is constructed to focus spin waves by a curved interface between two ferromagnetic thin films with different perpendicular magnetic anisotropies.
Mesoscale and Nanoscale Physics
Cross-domain Adaptation with Discrepancy Minimization for Text-independent Forensic Speaker Verification
Forensic audio analysis for speaker verification offers unique challenges due to location/scenario uncertainty and diversity mismatch between reference and naturalistic field recordings.
AIBench Training: Balanced Industry-Standard AI Training Benchmarking
We use real-world benchmarks to cover the factors space that impacts the learning dynamics to the most considerable extent.
AIBench: An Agile Domain-specific Benchmarking Methodology and an AI Benchmark Suite
An end-to-end benchmark is a distillation of the essential attributes of an industry-scale application.
AIBench: An Industry Standard Internet Service AI Benchmark Suite
On the basis of the AIBench framework, abstracting the real-world data sets and workloads from one of the top e-commerce providers, we design and implement the first end-to-end Internet service AI benchmark, which contains the primary modules in the critical paths of an industry scale application and is scalable to deploy on different cluster scales.
Air Quality Measurement Based on Double-Channel Convolutional Neural Network Ensemble Learning
In this paper, we propose a method for air quality measurement based on double-channel convolutional neural network ensemble learning to solve the problem of feature extraction for different parts of environmental images.
Image Captioning based on Deep Reinforcement Learning
However, in this paper, we propose a novel architecture for image captioning with deep reinforcement learning to optimize image captioning tasks.
Pulsed polarisation for robust DNP
We derive sequences theoretically and demonstrate experimentally that they are capable of efficient polarisation transfer from an optically polarised nitrogen-vacancy centre in diamond to the surrounding $^{13}$C nuclear spin bath even in the presence of control errors, making it an ideal tool for the realisation of the above NV centre based applications.
Quantum Physics
