News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — Machine Learning research 3d ago FB-GDM: Fully-Bayesian Guided Diffusion Models for High-Dimensional Linear Inverse Problems via Unsupervised Variational Inference arXiv:2609.29216v1 Announce Type: new Abstract: Diffusion models are powerful priors for linear inverse problems, but the reference guidance methods, Diffusion Posterior Sampling (DPS) and Pseudoinverse-Guided Diffusion Models ($\Pi$GDM), rely on scalar hyperparameters tuned per… 32 arXiv — Machine Learning research 3d ago BridgeMem: Causal Dyadic Transition Residuals for Temporal Knowledge Graph Forecasting arXiv:2609.29268v1 Announce Type: new Abstract: Temporal knowledge graph forecasting aims to infer future relational facts from the temporal structure of observed events. Existing forecasters mainly summarize history through entity states, relation states, paths, or exact… 4 arXiv — Machine Learning research 3d ago Learnable Time-Frequency Masks for Explaining Time-Series Classifiers arXiv:2609.29270v1 Announce Type: new Abstract: Time-series explainability remains challenging because discriminative information is often encoded in latent frequency or time-frequency features rather than in the raw signal itself. Existing attribution methods typically operate… 12 arXiv — Machine Learning research 3d ago Online Task Adaptation via Self-Organisation arXiv:2609.29281v1 Announce Type: new Abstract: Neural networks are typically adapted by computing gradients and updating model parameters. We investigate whether task-specific adaptation can instead emerge from a meta-learned self-organising process that requires no gradients… 26 arXiv — Machine Learning research 3d ago Beyond Feature Reliability: Repeat-Informed Multifractal Curve Regression for Brain-Age Prediction arXiv:2609.29307v1 Announce Type: new Abstract: Brain-age prediction from resting-state fMRI provides a quantitative framework for characterizing age-related changes in spontaneous brain dynamics and for identifying functional signatures. Existing studies have linked fractal and… 31 arXiv — Machine Learning research 3d ago Neuralized Multi-Wavelet Decomposition for Time Series Classification and Forecasting arXiv:2609.29317v1 Announce Type: new Abstract: Time series analysis is fundamental in domains such as finance, healthcare, and meteorology. Real-world time series often exhibit multiscale characteristics shaped by diverse latent factors, resulting in intricate temporal patterns… 32 arXiv — Machine Learning research 3d ago TinyCardioUNet: IMU-to-ECG Translation with Graph-Encoded Inter-Axis Dependencies and Tensor Decomposition-Based Parameter Reduction arXiv:2609.29322v1 Announce Type: new Abstract: Estimating electrocardiography (ECG) from a chest-worn inertial measurement unit (IMU) enables continuous heart rate (HR) monitoring without the discomfort of electrodes. We propose TinyCardioUNet, a lightweight UNet that uses all… 6 arXiv — Machine Learning research 3d ago FlowAtom: Atom-Based Evidence Aggregation for Multi-Label Website Fingerprinting arXiv:2609.29330v1 Announce Type: new Abstract: Identifying the set of monitored websites in mixed encrypted traffic is challenging because an individual flow often provides only partial evidence of website identity. To address this challenge, we propose FlowAtom, which… 10 arXiv — Machine Learning research 3d ago On the second-order optimization for spiking neural networks arXiv:2609.29379v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer an energy-efficient alternative to conventional neural networks by exploiting sparse, binary spikes, and event-driven computation. However, the training of SNNs remains challenging, as spiking… 35 arXiv — Machine Learning research 3d ago Lightweight Probabilistic Downscaling from a Deterministic Base Model arXiv:2609.29383v1 Announce Type: new Abstract: Climate data downscaling is the task of increasing the spatial resolution of climate data, typically by generating fine-resolution regional climate data from coarse global model output. Recent machine learning (ML) work in the… 5 arXiv — Machine Learning research 3d ago MORE-PLR: multi-output regression employed for partial label ranking arXiv:2609.29386v1 Announce Type: new Abstract: The partial label ranking problem is a supervised learning scenario that aims to fit a preference model that predicts a bucket order defined over a set of labels for a given input instance. This problem generalizes the well-known… 22 arXiv — Machine Learning research 3d ago ICE: Task-Aligned Clifford Latent Fields for Multimodal Graph Foundation Models arXiv:2609.29398v1 Announce Type: new Abstract: Multimodal attributed graphs connect entities, visual content, language, and observed relations. Learning one foundation across such graphs requires more than compressing each node into a fused Euclidean vector. The representation… 7 arXiv — Machine Learning research 3d ago Neural Transport Nested Sampling arXiv:2609.29413v1 Announce Type: new Abstract: Sampling from Boltzmann distributions of molecular systems is an inference problem that has seen significant recent developments fuelled by advances in neural density estimation. We develop a novel sampling algorithm, Neural… 24 arXiv — Machine Learning research 3d ago SPADE-DFL: Communication-Efficient Decentralized Federated Learning via Derivative-Free Linearized ADMM arXiv:2609.29446v1 Announce Type: new Abstract: Reducing communication in derivative-free decentralized learning requires controlling the disagreement accumulated over multiple local updates. This paper develops SPADE-DFL, a primal--dual method that allows the number of local… 26 arXiv — Machine Learning research 3d ago Decoupled Learning and Selection in Slate Recommendation for Privacy and Stability Under Noisy Scores arXiv:2609.29453v1 Announce Type: new Abstract: We formalize slate recommendation as a randomized score learner followed by deterministic selection. First, an appropriately scoped differential-privacy guarantee passes through selection and its audit trace by post-processing.… 30 arXiv — Machine Learning research 3d ago Precise Convergence Speed of Clipped SGD arXiv:2609.29458v1 Announce Type: new Abstract: We present a tightened convergence analysis of clipped gradient descent on $(L_0, L_1)$-smooth functions, with quantitative constants. Building on the ideas of Koloskova et al (2023), we refactor several case disjunctions to reveal… 30 arXiv — Machine Learning research 3d ago Direct Message Approximation (DMA): A Consistency-Based Framework for Tractable Approximate Inference on Factor Graphs arXiv:2609.29466v1 Announce Type: new Abstract: Approximate message passing on factor graphs underlies two dominant families of probabilistic inference algorithms: expectation propagation (EP) and variational message passing (VMP). Both methods approximate the marginal at each… 28 arXiv — Machine Learning research 3d ago BLADE: Distilled LLM Regularization for Calibrated Knowledge Graph Completion arXiv:2609.29487v1 Announce Type: new Abstract: Knowledge graph completion models optimize ranking, although many downstream applications require calibrated probabilities. We present BLADE, a variational model that separates latent truth from graph recording and distills offline… 37 arXiv — Machine Learning research 3d ago Task-Aware Spectral Pruning: A Mixture-of-Masks Framework for Efficient LLM Inference arXiv:2609.29499v1 Announce Type: new Abstract: Static pruning imposes one sparse structure on every prompt, even though reasoning, retrieval, generation, coding, and translation can depend on different parts of a language model. We introduce Task-Aware Spectral Pruning (TASP),… 11 arXiv — Machine Learning research 3d ago Spectral-Guided Diffusion: Accelerating Inference via Static Spectral Layer Scheduling arXiv:2609.29505v1 Announce Type: new Abstract: Diffusion inference repeatedly evaluates the same large network. We ask whether pretrained weights alone can identify residual branches that need not be recomputed throughout the trajectory. Our \textbf{Spectral Concentration Ratio… 18 arXiv — Machine Learning research 3d ago CataOPD: Catalytic On-Policy Distillation for Large Language Model Reasoning arXiv:2609.29518v1 Announce Type: new Abstract: Reinforcement learning (RL) and on-policy distillation (OPD) are two representative paradigms for improving large language model reasoning. However, when no correct trajectory is sampled, RL lacks a positive correctness signal,… 12 arXiv — Machine Learning research 3d ago Sample-Weighted End-to-End Trace-Norm Geometry for Multitask Learning arXiv:2609.29520v1 Announce Type: new Abstract: Multitask models combine a shared representation with task-specific outputs, but generalization bounds often control the two components separately. Such products can discard relative orientation and cancellation and can change… 38 arXiv — Machine Learning research 3d ago Common Covariance Geometry and Certification for Brownian Kernel Ladders arXiv:2609.29525v1 Announce Type: new Abstract: A representation-adaptive kernel class produces, on a fixed sample, a union of reproducing-kernel Hilbert-space ellipsoids rather than one ellipsoid. We introduce the minimum-trace common covariance that dominates the unrestricted… 6 arXiv — Machine Learning research 3d ago The Impossible Trinity of Time-Series Validation: A Conservation Law among Training Sufficiency, Test Coverage, and Temporal Causality arXiv:2609.29530v1 Announce Type: new Abstract: Validating a model on a time series asks for three things at once: each training run should use most of the sample (sufficiency), the test sets should together cover most of the sample (coverage), and training data should come… 5 arXiv — Machine Learning research 3d ago Generalized Graph Variational Autoencoders: Bounded Divergences Control Posterior Collapse arXiv:2609.29546v1 Announce Type: new Abstract: The variational graph autoencoder (VGAE) regularizes its posterior toward the prior with the Kullback-Leibler divergence, a choice inherited from the variational autoencoder rather than argued for. We introduce the generalized… 12 arXiv — Machine Learning research 3d ago Certified Predictive Value-of-Advice Gating for Cost-Aware Language-Model Guidance in Reinforcement Learning arXiv:2609.29548v1 Announce Type: new Abstract: Language-model advice can accelerate reinforcement learning, but calls are costly and returned actions may be stale or wrong. We formulate advice acquisition as a response-contingent metareasoning problem: before querying, the… 4 arXiv — Machine Learning research 3d ago Classifier-Dependent Benefits of Pseudo-Labeling for Semi-Supervised Android Malware Attribution arXiv:2609.29564v1 Announce Type: new Abstract: Detecting and classifying Android malware families remains challenging due to high feature dimensionality, class imbalance, and the high cost of expert-labeled data. Semi-supervised learning (SSL) offers a way to leverage unlabeled… 21 arXiv — Machine Learning research 3d ago When Identical Rows Disagree: From Benchmark Identifiability to Replication-Robust Anomaly Detection arXiv:2609.29580v1 Announce Type: new Abstract: A released table is often treated as an i.i.d. sample, although its repeated rows may encode business frequency, repeated entities, joins, resampling, or extraction errors. We show that this ambiguity creates a hidden measurement… 35 arXiv — Machine Learning research 3d ago A Computational Framework for Modelling Organisation-Level Semantic Identity from Longitudinal Textual Data arXiv:2609.29584v1 Announce Type: new Abstract: Organisations continuously generate large volumes of textual data that capture how they communicate, evolve and differentiate themselves over time. Although recent advances in natural language processing have substantially improved… 7 arXiv — Machine Learning research 3d ago Active Client Selection in Federated Trajectory Prediction with Uncertainty-Awareness and Heterogeneous Complexity arXiv:2609.29600v1 Announce Type: new Abstract: Training sequence models such as transformers is now standard for autonomous vehicle trajectory prediction, yet assembling high-quality centralized datasets remains challenging because real-world trajectories are fragmented across… 38 arXiv — Machine Learning research 3d ago Limited Structural Reliability in Public Educational Prediction Benchmarks: A Four-Dimension Audit of Seven Datasets arXiv:2609.29625v1 Announce Type: new Abstract: Across seven public educational prediction datasets, three passed all four pre-modeling reliability checks; the remaining four either failed group-aware generalization tests or lacked the provenance metadata needed to run them. One… 28 arXiv — Machine Learning research 3d ago A Manifold-Aware Topic Modeling Approach via Rank-Based Prototypes arXiv:2609.29630v1 Announce Type: new Abstract: Recent topic models leverage pretrained embeddings, but neural architectures produce latent representations without grounding in specific texts, and clustering-based pipelines assign representative documents only post hoc, relying… 14 arXiv — Machine Learning research 3d ago Graph, Loop, and Harness Engineering for Zero-Trust Agentic Data Engineering and Analytical Processing arXiv:2609.29668v1 Announce Type: new Abstract: Large language model agents increasingly automate data workflows, but end-to-end cloud data engineering and analytical execution require reliable coordination across code, data, infrastructure, and runtime environments. We present… 35 arXiv — Machine Learning research 3d ago GBFRVFL: Granular-Ball Computing-Based Fuzzy Random Vector Functional Link Network arXiv:2609.29670v1 Announce Type: new Abstract: In practical machine learning tasks, data are often contaminated with noise, outliers, and class imbalance, which can degrade the performance of conventional models. While random vector functional link (RVFL) networks offer fast… 5 arXiv — Machine Learning research 3d ago The Sequential Price of Continual Learning arXiv:2609.29674v1 Announce Type: new Abstract: Sequential task updates are fundamental to continual learning, but their recency bias can impose a lasting performance cost. We study this cost in an overparameterized linear-regression model with i.i.d. task sampling. We prove… 15 arXiv — Machine Learning research 3d ago Not All Synthetic Data Are Equal: Expert-Committee Audit Screening for Imbalanced Crash-Injury-Severity Prediction in Automated Driving Systems arXiv:2609.29687v1 Announce Type: new Abstract: Automated driving systems (ADSs) are increasingly operating on public roads, raising safety concerns, yet reliable prediction of crash injury severity remains difficult because crash reports are limited, severe outcomes are rare,… 32 arXiv — Machine Learning research 3d ago Predicting Symptoms of Amotivation and Anhedonia among University Students with a Novel Oversampling Method arXiv:2609.29690v1 Announce Type: new Abstract: University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social functioning, and overall well-being. Within this context, symptoms of… 36 arXiv — Machine Learning research 3d ago Bandit Multiclass PAC Learning: Corrected Lower Bounds, Exact Families, and a Confidence Direct-Sum Phenomenon arXiv:2609.29694v1 Announce Type: new Abstract: We study realizable multiclass PAC learning with bandit feedback: the learner observes an i.i.d. instance, predicts one of $K$ labels, and learns only whether the prediction was correct. Hanneke, Meng, Moran, and Shaeiri… 20 arXiv — Machine Learning research 3d ago An Agnostic Sample Compression Scheme for Squared Loss of Near-Linear Size in the Fat-Shattering Dimension arXiv:2609.29696v1 Announce Type: new Abstract: We construct, for every function class $\mathcal{F}\subseteq[0,1]^{\mathcal{X}}$ and every accuracy $0<\alpha\le 1$, an agnostic sample compression scheme for the empirical squared loss: for every finite sample… 22 arXiv — Machine Learning research 3d ago Safety-oriented pedestrian trajectory prediction at urban intersections using time-to-collision and crossing-zone context arXiv:2609.29706v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction is important for proactive road-safety applications, particularly at urban intersections where pedestrian motion is shaped by both vehicle interactions and crossing context. This study… 23 arXiv — Machine Learning research 3d ago Three Ways Classical Test Theory Misleads for LLM Judges arXiv:2609.29709v1 Announce Type: new Abstract: An LLM judge scores a bank of responses against a rubric, and the reliability comes back at $0.52$. What has been measured? Judge evaluation has begun borrowing reliability statistics from classical test theory, usually without… 14 arXiv — Machine Learning research 3d ago Decoupling Knowledge and Privacy: Post-Task Self-Distillation Replay for LLM Continual Learning arXiv:2609.29711v1 Announce Type: new Abstract: Privacy-preserving continual learning (PPCL) must reduce the reproduction of sensitive content while retaining useful knowledge across sequential tasks. Formal privacy guarantees characterize randomized mechanisms, whereas… 16 arXiv — Machine Learning research 3d ago Revalidation Beats Stateful Routing for Scientific Surrogates Under Distribution Shift arXiv:2609.29715v1 Announce Type: new Abstract: Surrogate models are often chosen during development and then left in place as new measurements arrive. That practice becomes risky when noise, input support, or physical parameters change. We asked whether such changes call for a… 29 arXiv — Machine Learning research 3d ago TopU-LBVS: A Realistic Multi Target Benchmark for Ligand Based Virtual Screening arXiv:2609.29740v1 Announce Type: new Abstract: Ligand-based virtual screening (LBVS) is a practical first-pass tool in early-stage drug discovery, but existing benchmarks can overestimate performance through random negatives, easy decoys, limited target coverage, and… 25 arXiv — Machine Learning research 3d ago WeatherDiagFlow: Evidence-Grounded Radar Nowcasting with Diagnostic Flow Refinement arXiv:2609.29772v1 Announce Type: new Abstract: Radar nowcasting is essential for short-term warning and emergency response, yet conventional systems mainly return future radar fields and provide limited support for operational communication and post-event verification. We… 31 arXiv — Machine Learning research 3d ago An Analytical Theory of Auxiliary Learning arXiv:2609.29774v1 Announce Type: new Abstract: Auxiliary learning is an optimization paradigm in which a neural network's performance on a target task is improved by jointly training it on additional tasks. However, the mechanisms behind this improvement remain poorly… 37 arXiv — Machine Learning research 3d ago FlashLoop: Fast and Memory-Efficient Looped Transformers via Lazy Updates arXiv:2609.29812v1 Announce Type: new Abstract: Looped Transformers have attracted substantial attention as a parameter-efficient approach to increasing computational depth through repeated application of shared Transformer blocks. However, their practical advantages over… 17 arXiv — Machine Learning research 3d ago SwitchPFN: Shared Switching Dynamics for Frozen In-Context Time Series Classification arXiv:2609.29814v1 Announce Type: new Abstract: Tabular foundation models (TFMs) provide a promising route to time-series classification, but their effectiveness depends on how sequential data are converted into tabular representations. Existing representations face two… 4 arXiv — Machine Learning research 3d ago From Graphs to Feeders: Constraint-Guided Diffusion for Rule-Compliant Feeder Generation arXiv:2609.29879v1 Announce Type: new Abstract: Generative modeling approaches often focus on recovering broad statistical characteristics from the training data. In the context of graph generation, this may refer to degree distributions, clustering coefficients, or spectral… 28 arXiv — Machine Learning research 3d ago Spatio-temporally complementary feature propagation on graphs for longitudinal AADT estimation arXiv:2609.29906v1 Announce Type: new Abstract: The estimation of Annual Average Daily Traffic (AADT) is vital for transportation planning and infrastructure maintenance, yet obtaining accurate values for an entire urban network across multiple years remains challenging due to… 17 Page 4 of 10 · 500 articles ← Newer Older →
