Paper List

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Summary of Feature Expansion and Enhanced Compression For Class Incremental Learning, by Quentin Ferdinand (ensta Bretagne et al.
Summary of Deepfmea — a Scalable Framework Harmonizing Process Expertise and Data-driven Phm, by Christoph Netsch et al.
Summary of Mitigating Federated Learning Contribution Allocation Instability Through Randomized Aggregation, by Arno Geimer et al.
Summary of A Galois Theorem For Machine Learning: Functions on Symmetric Matrices and Point Clouds Via Lightweight Invariant Features, by Ben Blum-smith et al.
Summary of Llm4ed: Large Language Models For Automatic Equation Discovery, by Mengge Du et al.
Summary of Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition, by Zhiyong Yang et al.
Summary of Decentralized Kernel Ridge Regression Based on Data-dependent Random Feature, by Ruikai Yang et al.
Summary of Data Imputation by Pursuing Better Classification: a Supervised Kernel-based Method, By Ruikai Yang et al.
Summary of Improved Bound For Robust Causal Bandits with Linear Models, by Zirui Yan et al.
Summary of Localizing Task Information For Improved Model Merging and Compression, by Ke Wang et al.
Summary of Quick and Accurate Affordance Learning, by Fedor Scholz et al.
Summary of Integrating Multi-physics Simulations and Machine Learning to Define the Spatter Mechanism and Process Window in Laser Powder Bed Fusion, by Olabode T. Ajenifujah et al.
Summary of Adaptive Exploration For Data-efficient General Value Function Evaluations, by Arushi Jain et al.
Summary of Constrained Exploration Via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics, by Haoyang Zheng et al.
Summary of Sample Selection Bias in Machine Learning For Healthcare, by Vinod Kumar Chauhan et al.
Summary of Rlhf Workflow: From Reward Modeling to Online Rlhf, by Hanze Dong et al.
Summary of Lai Loss: a Novel Loss For Gradient Control, by Yufei Lai
Summary of Almanac Copilot: Towards Autonomous Electronic Health Record Navigation, by Cyril Zakka et al.
Summary of All Nodes Are Created Not Equal: Node-specific Layer Aggregation and Filtration For Gnn, by Shilong Wang et al.
Summary of Distribution Learning Meets Graph Structure Sampling, by Arnab Bhattacharyya et al.
Summary of Imafd: An Interpretable Multi-stage Approach to Flood Detection From Time Series Multispectral Data, by Ziyang Zhang et al.
Summary of Stable Diffusion-based Data Augmentation For Federated Learning with Non-iid Data, by Mahdi Morafah et al.
Summary of Active Learning with Simple Questions, by Vasilis Kontonis et al.
Summary of Sensitivity Analysis For Active Sampling, with Applications to the Simulation Of Analog Circuits, by Reda Chhaibi et al.
Summary of Semantic Loss Functions For Neuro-symbolic Structured Prediction, by Kareem Ahmed et al.
Summary of Intrinsic Fairness-accuracy Tradeoffs Under Equalized Odds, by Meiyu Zhong et al.
Summary of Cafa: Global Weather Forecasting with Factorized Attention on Sphere, by Zijie Li et al.
Summary of Indoor Pm2.5 Forecasting and the Association with Outdoor Air Pollution: a Modelling Study Based on Sensor Data in Australia, by Wenhua Yu et al.
Summary of Binning As a Pretext Task: Improving Self-supervised Learning in Tabular Domains, by Kyungeun Lee et al.
Summary of Structured Reinforcement Learning For Incentivized Stochastic Covert Optimization, by Adit Jain and Vikram Krishnamurthy
Summary of Nonparametric Sparse Online Learning Of the Koopman Operator, by Boya Hou et al.
Summary of Reducing Spatial Discretization Error on Coarse Cfd Simulations Using An Openfoam-embedded Deep Learning Framework, by Jesus Gonzalez-sieiro et al.
Summary of Can Language Models Explain Their Own Classification Behavior?, by Dane Sherburn et al.
Summary of Honeybee: a Scalable Modular Framework For Creating Multimodal Oncology Datasets with Foundational Embedding Models, by Aakash Tripathi et al.
Summary of Boosting House Price Estimations with Multi-head Gated Attention, by Zakaria Abdellah Sellam et al.
Summary of Intrinsic Rewards For Exploration Without Harm From Observational Noise: a Simulation Study Based on the Free Energy Principle, by Theodore Jerome Tinker et al.
Summary of Towards Marginal Fairness Sliced Wasserstein Barycenter, by Khai Nguyen and Hai Nguyen and Nhat Ho
Summary of Predictive Modeling Of Flexible Ehd Pumps Using Kolmogorov-arnold Networks, by Yanhong Peng et al.
Summary of Towards Subgraph Isomorphism Counting with Graph Kernels, by Xin Liu et al.
Summary of Sparse Domain Transfer Via Elastic Net Regularization, by Jingwei Zhang et al.
Summary of Restad: Reconstruction and Similarity Based Transformer For Time Series Anomaly Detection, by Ramin Ghorbani et al.
Summary of Perflow: Piecewise Rectified Flow As Universal Plug-and-play Accelerator, by Hanshu Yan et al.
Summary of Train Faster, Perform Better: Modular Adaptive Training in Over-parameterized Models, by Yubin Shi et al.
Summary of Distributed High-dimensional Quantile Regression: Estimation Efficiency and Support Recovery, by Caixing Wang et al.
Summary of Glira: Black-box Membership Inference Attack Via Knowledge Distillation, by Andrey V. Galichin et al.
Summary of Accelerating the Evolution Of Personalized Automated Lane Change Through Lesson Learning, by Jia Hu et al.
Summary of Evaluating the Explainable Ai Method Grad-cam For Breath Classification on Newborn Time Series Data, by Camelia Oprea et al.
Summary of On-device Online Learning and Semantic Management Of Tinyml Systems, by Haoyu Ren et al.
Summary of Noisebench: Benchmarking the Impact Of Real Label Noise on Named Entity Recognition, by Elena Merdjanovska et al.
Summary of Analysis Of the Rate Of Convergence Of An Over-parametrized Convolutional Neural Network Image Classifier Learned by Gradient Descent, By Michael Kohler et al.
Summary of Towards Adaptive Imfs — Generalization Of Utility Functions in Multi-agent Frameworks, by Kaushik Dey et al.
Summary of Anomalyllm: Few-shot Anomaly Edge Detection For Dynamic Graphs Using Large Language Models, by Shuo Liu et al.
Summary of Near-optimal Regret in Linear Mdps with Aggregate Bandit Feedback, by Asaf Cassel and Haipeng Luo and Aviv Rosenberg and Dmitry Sotnikov
Summary of Hyperparameter Importance Analysis For Multi-objective Automl, by Daphne Theodorakopoulos et al.
Summary of Squeezing Lemons with Hammers: An Evaluation Of Automl and Tabular Deep Learning For Data-scarce Classification Applications, by Ricardo Knauer et al.
Summary of Class-wise Activation Unravelling the Engima Of Deep Double Descent, by Yufei Gu
Summary of Establishing a Unified Evaluation Framework For Human Motion Generation: a Comparative Analysis Of Metrics, by Ali Ismail-fawaz and Maxime Devanne and Stefano Berretti and Jonathan Weber and Germain Forestier
Summary of Foresee: Multimodal and Multi-view Representation Learning For Robust Prediction Of Cancer Survival, by Liangrui Pan et al.
Summary of Secure Aggregation Meets Sparsification in Decentralized Learning, by Sayan Biswas et al.
Summary of Usp: a Unified Sequence Parallelism Approach For Long Context Generative Ai, by Jiarui Fang and Shangchun Zhao
Summary of Neural Network Compression For Reinforcement Learning Tasks, by Dmitry A. Ivanov et al.
Summary of Deephydra: Resource-efficient Time-series Anomaly Detection in Dynamically-configured Systems, by Franz Kevin Stehle et al.
Summary of Integrating Supervised and Unsupervised Learning Approaches to Unveil Critical Process Inputs, by Paris Papavasileiou et al.
Summary of Cages: Cost-aware Gradient Entropy Search For Efficient Local Multi-fidelity Bayesian Optimization, by Wei-ting Tang and Joel A. Paulson
Summary of Chebyshev Polynomial-based Kolmogorov-arnold Networks: An Efficient Architecture For Nonlinear Function Approximation, by Sidharth Ss et al.
Summary of On-demand Model and Client Deployment in Federated Learning with Deep Reinforcement Learning, by Mario Chahoud et al.
Summary of Unified Video-language Pre-training with Synchronized Audio, by Shentong Mo et al.
Summary of On Discovery Of Local Independence Over Continuous Variables Via Neural Contextual Decomposition, by Inwoo Hwang et al.
Summary of Ensemble Successor Representations For Task Generalization in Offline-to-online Reinforcement Learning, by Changhong Wang et al.
Summary of Oxygenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning, by Bin Lu et al.
Summary of Adaptive Control Of Recurrent Neural Networks Using Conceptors, by Guillaume Pourcel et al.
Summary of A Supervised Information Enhanced Multi-granularity Contrastive Learning Framework For Eeg Based Emotion Recognition, by Xiang Li et al.
Summary of Universal Batch Learning Under the Misspecification Setting, by Shlomi Vituri and Meir Feder
Summary of Human-interpretable Clustering Of Short-text Using Large Language Models, by Justin K. Miller et al.
Summary of Valid: a Validated Algorithm For Learning in Decentralized Networks with Possible Adversarial Presence, by Mayank Bakshi et al.
Summary of Erasing Concepts From Text-to-image Diffusion Models with Few-shot Unlearning, by Masane Fuchi et al.
Summary of Machine Unlearning in Contrastive Learning, by Zixin Wang and Kongyang Chen
Summary of Liquid Ensemble Selection For Continual Learning, by Carter Blair et al.
Summary of Stochastic Bandits with Relu Neural Networks, by Kan Xu et al.
Summary of Tkan: Temporal Kolmogorov-arnold Networks, by Remi Genet and Hugo Inzirillo
Summary of Medconceptsqa: Open Source Medical Concepts Qa Benchmark, by Ofir Ben Shoham et al.
Summary of Forecasting with An N-dimensional Langevin Equation and a Neural-ordinary Differential Equation, by Antonio Malpica-morales et al.
Summary of Incorporating Anatomical Awareness For Enhanced Generalizability and Progression Prediction in Deep Learning-based Radiographic Sacroiliitis Detection, by Felix J. Dorfner et al.
Summary of Conformalized Survival Distributions: a Generic Post-process to Increase Calibration, by Shi-ang Qi et al.
Summary of Revisiting the Efficacy Of Signal Decomposition in Ai-based Time Series Prediction, by Kexin Jiang et al.
Summary of Robust Model Aggregation For Heterogeneous Federated Learning: Analysis and Optimizations, by Yumeng Shao et al.
Summary of Ressurv: Cancer Survival Analysis Prediction Model Based on Residual Networks, by Wankang Zhai
Summary of Grasp-gcn: Graph-shape Prioritization For Neural Architecture Search Under Distribution Shifts, by Sofia Casarin et al.
Summary of Fair Graph Representation Learning Via Sensitive Attribute Disentanglement, by Yuchang Zhu et al.
Summary of Bayesian Frequency Estimation Under Local Differential Privacy with An Adaptive Randomized Response Mechanism, by Soner Aydin and Sinan Yildirim
Summary of Dtmamba : Dual Twin Mamba For Time Series Forecasting, by Zexue Wu and Yifeng Gong and Aoqian Zhang
Summary of Predictive Modeling in the Reservoir Kernel Motif Space, by Peter Tino et al.
Summary of Demystifying the Hypercomplex: Inductive Biases in Hypercomplex Deep Learning, by Danilo Comminiello et al.
Summary of Lasso Ridge Based Xgboost and Deep_lstm Help Tennis Players Perform Better, by Wankang Zhai et al.
Summary of Decoding Cognitive Health Using Machine Learning: a Comprehensive Evaluation For Diagnosis Of Significant Memory Concern, by M. Sajid et al.
Summary of Llms and the Future Of Chip Design: Unveiling Security Risks and Building Trust, by Zeng Wang et al.
Summary of Learning Flame Evolution Operator Under Hybrid Darrieus Landau and Diffusive Thermal Instability, by Rixin Yu et al.
Summary of Auditing An Automatic Grading Model with Deep Reinforcement Learning, by Aubrey Condor et al.
Summary of Data-efficient and Robust Task Selection For Meta-learning, by Donglin Zhan and James Anderson
Summary of Diffusion Models As Probabilistic Neural Operators For Recovering Unobserved States Of Dynamical Systems, by Katsiaryna Haitsiukevich et al.