Conference Schedule

Final Schedule

11 November 2023
08:30 - Registration desk open (Ground Floor)
09:00 - 10:30Tutorial #01: Mathematical Guarantees for Fairness in Reinforcement Learning (Room: A203)
09:00 - 10:30Tutorial #02: Neural Program Synthesis and Induction (Room: A204)
09:00 - 10:30Tutorial #03: Trustworthy Learning Under Imperfect Data (Room: A207)
10:30 - 11:00Coffee break (2nd Floor: In between Room A203 & Room A204)
11:00 - 12:30Tutorial #01: Mathematical Guarantees for Fairness in Reinforcement Learning (Room: A203)
11:00 - 12:30Tutorial #02: Neural Program Synthesis and Induction (Room: A204)
11:00 - 12:30Tutorial #03: Trustworthy Learning Under Imperfect Data (Room: A207)
12:30 - 13:30Lunch break (Ground Floor: Cafe Aplus)
13:30 - 15:30Workshop #01: New Horizons of Online Learning (Room: A203)
13:30 - 15:30Workshop #02: Pattern Recognition in Healthcare Analytics (PRHA) (Room: A204)
15:30 - 16:00Coffee break (2nd Floor: In between Room #A203 and Room #A204)
16:00 - 18:00Workshop #01: New Horizons of Online Learning (Room: A203)
16:00 - 18:00Workshop #02: Pattern Recognition in Healthcare Analytics (PRHA) (Room: A204)
18:00 - 19:00Welcome reception(2nd Floor: In between Room A203 and Room A204)
12 November 2023
08:00 - Registration desk open (Ground Floor)
08:30 - 10:00Oral presentation session #01: Computer Vision I (Room: A203)
  • 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
08:30 - 10:00Oral presentation session #02: Applications I (Room: A204)
  • 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
08:30 - 10:00Oral presentation session #03: Machine Learning Theory I (Room: A207)
  • 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
10:00 - 10:30Coffee break (2nd Floor: In between Room A203 and Room A204)
10:30 - 11:40Oral presentation session #04: Computer Vision II - Document and Language Understanding (Room: A203)
  • 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
10:30 - 11:40Oral presentation session #05: Applications II - Transportation and Navigation (Room: A204)
  • 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
10:30 - 11:40Oral presentation session #06: Self-Supervised and Generative Models (Room: A207)
  • 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
11:45 - 12:45Invited talk #01: Foundation Models for Life Science by Le Song (Room: Conference Hall)
12:45 - 13:45Lunch break (Ground Floor: Cafe Aplus)
13:45 - 14:45Invited talk #02: SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning by Nancy F. Chen (Room: Conference Hall)
15:00 - 16:30Oral presentation session #07: Computer Vision III - Biomedical and Biometric Applications (Room: A203)
  • 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
15:00 - 16:30Oral presentation session #08: Trustworthy Machine Learning I (Room: A204)
  • 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
15:00 - 16:30Oral presentation session #09: Machine Learning Theory II (Room: A207)
  • 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
16:30 - 17:00Coffee break (2nd Floor: In between Room A203 and Room A204)
17:00 - 18:20Oral presentation session #10: Graph Machine Learning (Room: A203)
  • 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
17:00 - 18:40Oral presentation session #11: Machine Learning Theory III (Room: A204)
  • 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
18:30 - 20:30Poster presentation session (2nd Floor: In between Room A203 and Room A204)
13 November 2023
08:00 - Registration desk open (Ground Floor)
08:30 - 10:00Oral presentation session #12: Computer Vision IV (Room: Conference Hall)
  • 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
10:00 - 10:30Coffee break (In front of Conference Hall)
10:30 - 12:00Oral presentation session #13: Natural Language Understanding and Computer Vision (Room: Conference Hall)
  • 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
12:00 - 13:00Invited talk #03: Beyond Test Accuracies for Studying Deep Neural Networks by Kyunghyun Cho (Room: Conference Hall)
13:00 - 14:00Lunch break (Ground Floor: Cafe Aplus)
14:00 - 15:45Oral presentation session #14: New Architectures and Algorithms (Room: Conference Hall)
  • 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
15:30 - 16:00Coffee break (In front on Conference Hall)
16:00 - 17:30Oral presentation session #15: Generative, Unsupervised, and Semi-Supervised Models (Room: Conference Hall)
  • 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
17:30 - 18:00Transfer to conference banquet
18:00 - 20:30Conference banquet (Develi Ataşehir Restaurant)
20:30 - 21:00Transfer to conference center
14 November 2023
08:00 - Registration desk open (Ground Floor)
08:30 - 10:15Oral presentation session #16: Model Efficiency and Adaptation (Room: Conference Hall)
  • 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
10:15 - 10:45Coffee break (In front of Conference Hall)
10:45 - 12:00Oral presentation session #17: Graph Learning and Learning with Kernels (Room: Conference Hall)
  • 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
12:00 - 13:00Invited talk #04: Details or Artifacts: Solving Inverse Problems in Image/Video Processing in the Era of Deep Learning by Murat Tekalp (Room: Conference Hall)
13:00 - 14:00Lunch break (Ground Floor: Cafe Aplus)
14:00 - 15:45Oral presentation session #18: Trustworthy Machine Learning II (Room: Conference Hall)
  • 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
15:45 - 16:15Coffee break (In front of Conference Hall)
16:15 - 17:30Oral presentation session #19: Reinforcement Learning and Robust Learning Algorithms (Room: Conference Hall)
  • 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
17:30 - 18:00Closing ceremony (Room: Conference Hall)