ACML 2023

11 November 2023

12 November 2023

• Paper #162: Simple and Efficient Vision Backbone Adapter for Image Semantic Segmentation
• Paper #454: Robust Image Classification via Using Multiple Diversity Losses
• Paper #239: The Importance of Anti-Aliasing in Tiny Object Detection
• Paper #325: Self-Supervised Example Difficulty Balancing for Local Descriptor Learning
• Paper #61: Knowledge-Aware Image Understanding with Multi-Level Visual Representation Enhancement for Visual Question Answering
• Paper #115: Compositional Scene Modeling with Global Object-Centric Representations
• Paper #314: A Simple and General Binarization Method for Image Restoration Neural Networks
• Paper #145: Deep Uniformly Distributed Centers on a Hypersphere for Open Set Recognition
• Paper #279: GWQ: Group-Wise Quantization Framework for Neural Networks

• Paper #336: Unveiling the Power of Self-Attention for Shipping Cost Prediction: The Rate Card Transformer
• Paper #393: Frequency-Dependent Image Reconstruction Error for Micro Defect Detection
• Paper #278: Remote Wildfire Detection Using Multispectral Satellite Imagery and Vision Transformers
• Paper #402: Mem-Rec: Memory Efficient Recommendation System Using Alternative Representation
• Paper #355: Multi-Behavior Session-Based Recommendation via Graph Reinforcement Learning
• Paper #310: TFAN: Temporal-Feature Correlations Attention-Based Network for Urban Air Quality Prediction Using Data Fusion Technology
• Paper #269: Enhancing Cross-Category Learning in Recommendation Systems with Multi-Layer Embedding Training
• Paper #67: Applied Machine Learning to the Determination of Biochar Hydrogen Sulfide Adsorption Capacity
• Paper #380: DataWise: Solve partial differential equations with a probabilistic model

• Paper #55: Margin Distribution and Structural Diversity Guided Ensemble Pruning
• Paper #69: Sanitized Clustering Against Confounding Bias
• Paper #9: Reduced Implication-Bias Logic Loss for Neuro-Symbolic Learning
• Paper #275: Overcoming Catastrophic Forgetting with Classifier Expander
• Paper #313: Revisiting Structured Dropout
• Paper #264: A Pragmatic Look at Deep Imitation Learning
• Paper #406: Ted: Tree Delineation with Reduced Dimensions Using Entropy and Deep Learning
• Paper #211: Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee
• Paper #403: Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain

• Paper #33: Chinese Character Recognition with Radical-Structured Stroke Trees
• Paper #446: Efficient Medical Images Text Detection with Vision-Language Pre-training Approach
• Paper #263: Long-Range Graph U-Nets: Node and Edge Clustering Pooling Model For Stroke Classification in Online Handwritten Documents
• Paper #158: Understanding More Knowledge Makes the Transformer Perform Better in Document-Level Relation Extraction
• Paper #292: VMLC: Statistical Process Control for Image Classification in Manufacturing
• Paper #344: Single Image Super-Resolution Based on Non-Subsampled Shearlet Transform
• Paper #229: Show Me How It's Done: The Role of Explanations in Fine-Tuning Language Models

• Paper #243: Lost and Found: How Self-Supervised Learning Helps GPS Coordinates Find Their Way
• Paper #262: Reinforcement Learning for Solving Stochastic Vehicle Routing Problem
• Paper #217: Multi-Objective Adaptive Dynamics Attention Model to Solve Multi-Objective Vehicle Routing Problem
• Paper #277: Faster Target Encirclement with Utilization of Obstacles via Multi-Agent Reinforcement Learning
• Paper #419: KURL: A Knowledge-Guided Reinforcement Learning Model for Active Object Tracking
• Paper #345: Deep Traffic Benchmark: Aerial Perception and Driven Behavior Dataset
• Paper #188: Learning to Terminate in Object Navigation

• Paper #27: Learning Sample-Aware Confidence Threshold for Semi-Supervised Learning
• Paper #251: Self Weighted Multiplex Modularity Maximization for Multiview Clustering
• Paper #413: How GAN Generators Can Invert Networks in Real-Time
• Paper #208: Folded Hamiltonian Monte Carlo for Bayesian Generative Adversarial Networks
• Paper #322: SANGEA: Scalable and Attributed Network Generation
• Paper #254: Diffusion-Based Visual Representation Learning for Medical Question Answering
• Paper #289: Improving Denoising Diffusion Models via Simultaneous Estimation of Image and Noise

• Paper #216: FusionU-Net: U-Net with Enhanced Skip Connection for Pathology Image Segmentation
• Paper #161: SART-Res-UNet: Fan Beam CT Image Reconstruction from Limited Projections Using Attention-Enabled Residual U-Net
• Paper #157: Automatic Segmentation of Aortic and Mitral Valves for Heart Surgery Planning of Hypertrophic Obstructive Cardiomyopathy
• Paper #204: Meta-Forests: Domain Generalization on Random Forest with Meta-Learning
• Paper #339: Ada2NPT: An Adaptive Nearest Proxies Triplet Loss for Attribute-Aware Face Recognition with Adaptively Compacted Feature Learning
• Paper #321: FasterVoxelPose+: Fast and Accurate Voxel-Based 3D Human Pose Estimation by Depth-Wise Projection Decay
• Paper #259: Early Diagnosis of Alzheimer through Swin-Transformer-Based Deep Learning Framework Using Sparse Diffusion Measures
• Paper #375: Pedestrian Cross Forecasting with Hybrid Feature Fusion
• Paper #390: Temporal Shift - Multi-Objective Loss Function for Improved Anomaly Fall Detection

• Paper #265: Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings
• Paper #423: Mitigating Bias: Enhancing Image Classification by Improving Model Explanations
• Paper #210: Transformed Gaussian Processes for Characterizing a Model's Discrepancy
• Paper #324: ASAP: Attention-Based State Space Abstraction for Policy Summarization
• Paper #34: Outlier Robust Adversarial Training
• Paper #448: DENL: Diverse Ensemble and Noisy Logits for Improved Robustness of Neural Networks
• Paper #248: Detecting and Repairing Deviated Outputs of Compressed Models
• Paper #256: Estimation of Counterfactual Interventions Under Uncertainties
• Paper #434: An Empirical Study of Federated Unlearning: Efficiency and Effectiveness

• Paper #74: Online Binary Classification from Similar and Dissimilar Data
• Paper #98: Generation, Augmentation, and Alignment: A Pseudo-Source Domain Based Method for Source-Free Domain Adaptation
• Paper #79: Communication-Efficient Clustered Federated Learning via Model Distance
• Paper #298: Better Loss Landscape Visualization for Deep Neural Networks with Trajectory Information
• Paper #54: Equilibrium Point Learning
• Paper #399: Facto-CNN: Memory-Efficient CNN Training with Low-rank Tensor Factorization and Lossy Tensor Compression
• Paper #247: Maximization of Minimum Weighted Hamming Distance between Set Pairs
• Paper #305: A Multi-Surrogate Assisted Salp Swarm Feature Selection Algorithm with Multi-Population Adaptive Generation Strategy for Classification
• Paper #102: Bayesian Tensor Factorisations for Time Series of Counts

• Paper #134: A New Perspective on the Expressive Equivalence Between Graph Convolution and Attention Models
• Paper #168: Dynamic Offset Metric on Heterogeneous Information Networks for Cold-Start Recommendation
• Paper #386: Probing Traffic Trend Forecasting via Spatial-Temporal Aware Learning-Graph Attention
• Paper #294: Degree-Based Stratification of Nodes in Graph Neural Networks
• Paper #383: Unleashing the Power of High-Pass Filtering in Continuous Graph Neural Networks
• Paper #149: Graph Structure Learning via Lottery Hypothesis at Scale
• Paper #309: Hybrid Convolution Method for Graph Classification Using Hierarchical Topology Feature
• Paper #414: K-Truss Based Temporal Graph Convolutional Network for Dynamic Graphs

• Paper #364: Optimal Nonlinearities Improve Generalization Performance of Random Features
• Paper #416: Prototypical Model with Information-Theoretic Loss Functions for Generalized Zero-Shot Learning
• Paper #274: Selective Nonparametric Regression via Testing
• Paper #270: Federated Learning with Uncertainty via Distilled Predictive Distributions
• Paper #431: A Partially Observable Monte Carlo Planning Algorithm Based on Path Modification
• Paper #433: Intractability of Learning the Discrete Logarithm with Gradient-Based Methods
• Paper #342: Domain Generalization with Interpolation Robustness
• Paper #164: Evolutionary Neural Architecture Search for Multivariate Time Series Forecasting
• Paper #14: Understanding Imbalanced Data: XAI & Interpretable ML Framework
• Paper #227: Adaptive Riemannian Stochastic Gradient Descent and Reparameterization for Gaussian Mixture Model Fitting

13 November 2023

• Paper #82: Task-Decoupled Interactive Embedding Network for Object Detection
• Paper #288: Edit-A-Video: Single Video Editing with Object-Aware Consistency
• Paper #100: Multi-Label Image Classification with Multi-Layered Multi-Perspective Dynamic Semantic Representation
• Paper #252: Temporal RPN Learning Strategy for Weakly-Supervised Temporal Action Localization
• Paper #323: Enhancing Model Generalization for Cervical Fluid-Based Cell Detection through Causal Feature Extraction: A Novel Method
• Paper #224: Robust Blind Watermarking Framework for Hybrid Networks Combining CNN and Transformer

• Paper #167: State Value Generation with Prompt Learning and Self-Training for Low-Resource Dialogue State Tracking
• Paper #199: A Novel Counterfactual Data Augmentation Method for Aspect-Based Sentiment Analysis
• Paper #453: Hyper-Label-Graph: Modeling Branch-Level Dependencies of Labels for Hierarchical Multi-Label Text Classification
• Paper #83: Scalable Variable Selection for Two-View Learning Tasks with Projection Operators
• Paper #117: A Neural Meta-Model for Predicting Winter Wheat Crop Yield
• Paper #59: Hierarchical U-Net with Re-Parameterization Technique for Spatio-Temporal Weather Forecasting

• Paper #297: Training a General Spiking Neural Network with Improved Efficiency and Minimum Latency
• Paper #96: Structural Causal Models Reveal Confounder Bias in Linear Program Modelling
• Paper #343: Can Infinitely Wide Deep Nets Help Small-Data Multi-Label Learning?
• Paper #291: Decouple then Combine: A Simple and Effective Framework for Fraud Transaction Detection
• Paper #97: Learning De-Biased Regression Trees and Forests from Complex Samples
• Paper #43: Hybrid Acceleration Techniques for the Physics-Informed Neural Networks: A Comparative Analysis
• Paper #128: Cell Variational Information Bottleneck Network

• Paper #140: Generative Semi-Supervised Learning with Meta-Optimized Synthetic Samples
• Paper #307: ProtoDiffusion: Classifier-Free Diffusion Guidance with Prototype Learning
• Paper #178: Cross-Domain Relation Adaptation
• Paper #147: Q-Match: Self-Supervised Learning by Matching Distributions Induced by a Queue
• Paper #189: Patch-Level Neighborhood Interpolation: A General and Effective Graph-Based Regularization Strategy
• Paper #359: Attributed Graph Subspace Clustering with Graph-Boosting

14 November 2023

• Paper #75: Neural Network Structure Simplification by Assessing Evolution in Node Weight Magnitude
• Paper #358: Free Energy of Bayesian Convolutional Neural Network with Skip Connection
• Paper #40: Exploiting Counter-Examples for Active Learning with Partial-labels
• Paper #24: Tracking Treatment Effect Heterogeneity in Evolving Environments
• Paper #301: A Mixed-Precision Quantization Method without Accuracy Degradation Using Semilayers
• Paper #35: Better Schedules for Low Precision Training of Deep Neural Networks
• Paper #238: Harmonic-NAS: Hardware-Aware Multimodal Neural Architecture Search on Resource-Constrained Devices

• Paper #319: Distilling Influences to Mitigate Prediction Churn in Graph Neural Networks
• Paper #130: Graph Contrastive Learning with Group Whitening
• Paper #169: A Corrected Expected Improvement Acquisition Function Under Noisy Observations
• Paper #337: Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory
• Paper #371: Deep Kernel Regression with Finite Learnable Kernels

• Paper #49: Explaining Neural Networks without Access to Training Data
• Paper #385: Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation
• Paper #93: Advancing Deep Metric Learning With Adversarial Robustness
• Paper #143: Towards Better Explanations for Object Detection
• Paper #116: Style Spectroscope: Improve Interpretability and Controllability Through Fourier Analysis
• Paper #391: The Fine Print on Tempered Posteriors
• Paper #77: NRAT: Towards Adversarial Training with Inherent Label Noise

• Paper #389: BarlowRL: Barlow Twins for Data Efficient Reinforcement Learning
• Paper #219: Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games
• Paper #425: Deep Reinforcement Learning for Two-Sided Online Bipartite Matching in Collaborative Order Picking
• Paper #280: Thompson Exploration with Best Challenger Rule in Best Arm Identification
• Paper #426: Logarithmic Regret in Communicating MDPs: Leveraging Known Dynamics with Bandits