githubGitHubあり2026-09-08
smile — Statistical Machine Intelligence & Learning Engine
マシン学習、統計学習などに関する統計的エンジンです。
自然言語処理大規模言語モデル分類回帰画像
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「regression」の検索結果
60 件arxivPaper only2026-09-04
Optimal Rates for Agentic Networked Information Aggregation
Building on the pioneering paper of Kearns, Roth, and Ryu (SODA'26), we study information aggregation in a net
コンピュータビジョンセグメンテーション分類回帰
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- Hard
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arxivPaper only2026-09-04
Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar
Late Gadolinium Enhancement (LGE) on cardiac magnetic resonance is a key marker of myocardial scar, but its li
表形式向きCPUで試しやすい深層学習Transformer分類回帰
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- Hard
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arxivPaper only2026-09-04
FluxDisco: Symbolic Regression for Stoichiometric Dynamical Systems via Monte Carlo Graph Search
Dynamical symbolic regression methods identify governing differential equations from noisy data, balancing int
説明可能自然言語処理RAG回帰
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arxivPaper only2026-09-04
Beyond Homoscedasticity: Decoupled Uncertainty Optimization for Deep Imbalanced Regression
Deep Imbalanced Regression (DIR) is pervasive in continuous prediction tasks across diverse modalities, such a
少数データ向き深層学習Transformer回帰画像
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- Hard
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arxivGitHubあり2026-09-04
Adaptation Interfaces for In-Context Tabular Foundation Models in Time-to-Event Prediction
Tabular foundation models (TabFMs) achieve strong performance on structured data, particularly for standard cl
表形式向き自然言語処理ファインチューニング分類回帰テキスト
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- Hard
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arxivPaper only2026-09-04
LookThere! Sparse Vision by Reinforced Selection
Vision transformers typically treat every image token as equally important, yet for most tasks in computer vis
深層学習Transformer分類セグメンテーション回帰
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- Hard
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arxivPaper only2026-09-04
WEECFP-SuRGE: Wide Embedded Extended Connectivity Fingerprint with Substructure Rotary Graph-distance Encoding
We introduce WEECFP, a parameter-free 1024-dimensional continuous molecular fingerprint that scatters each Mor
MI向き深層学習Transformer回帰
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arxivPaper only2026-09-04
SMILE: Bridging Continuous Optimization and Discrete Symbolic Recovery
Symbolic regression (SR) discovers closed-form mathematical expressions from data, offering interpretability b
説明可能深層学習軽量化・量子化回帰
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arxivPaper only2026-09-04
Reconciling Universal and Uniform Learning with $Q$-Aggregation
We study regression under bounded responses in terms of excess mean squared error. When the comparator class i
深層学習軽量化・量子化回帰
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- Hard
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arxivPaper only2026-09-04
Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models
Large language models (LLMs) are increasingly evaluated on molecular property benchmarks, but accuracy cannot
MI向き自然言語処理大規模言語モデル回帰テキスト
- 用途
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- 難易度
- Hard
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arxivPaper only2026-09-04
TreeFI: Value-Aware Statistical Fault Injection for Deep Neural Networks
Reliability evaluation of deep neural networks under hardware faults commonly relies on fault injection, but e
深層学習Transformer回帰画像
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- Hard
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arxivPaper only2026-09-04
SimFuse3D: Source-Guided Target Simulation and Confidence-Guided Multi-Stage Localization Reweighting for Cross-Platform 3D Object Detection
Changes in sensor height and viewpoint alter object-level point distributions, making cross-platform LiDAR uns
センサ/時系列深層学習CNN検出回帰3D
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- Hard
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arxivPaper only2026-09-04
Long Horizon Transformer Quantile Fault Prediction for Multi Site Industrial Predictive Maintenance
Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal ope
センサ/時系列品質予測/異常検知深層学習Transformer分類回帰テキスト
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- Hard
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arxivPaper only2026-09-03
Mitra-v2 Technical Report
We introduce Mitra-v2, a tabular foundation model that delivers state-of-the-art performance on real-world cla
表形式向きセンサ/時系列深層学習Transformer分類検出回帰
- 用途
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- Hard
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arxivPaper only2026-09-03
Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks
Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accur
強化学習マルチエージェント分類回帰
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- Hard
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arxivPaper only2026-09-03
RATL: Learning from Retrieved Residuals for Robust Multivariate Time-Series Forecasting
Retrieval-augmented generation (RAG) complements parametric models with retrieved external evidence. The same
センサ/時系列深層学習Transformer生成回帰予測
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- Hard
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arxivPaper only2026-09-03
Landmark-Based Discrimination of Injury-Associated Athlete-Sessions from Minute-Resolution Multimodal Football Monitoring Data
Athlete monitoring data may be recorded minute by minute throughout a match or training session, while injury
表形式向きCPUで試しやすい深層学習Transformer回帰マルチモーダル
- 用途
- 回帰
- 難易度
- Hard
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arxivPaper only2026-09-03
Federated Causal Discovery via Regression-Directed Cumulants
In this paper we study linear non-Gaussian acyclic models (LiNGAM) when used in federated environments. These
コンピュータビジョンセグメンテーション回帰
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- 難易度
- Hard
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arxivGitHubあり2026-09-03
Efficient Constant Optimization for Symbolic Regression with GPU-Accelerated Tree-Based Genetic Programming
Constant optimization refines the numerical coefficients of candidate expressions in tree-based genetic progra
品質予測/異常検知深層学習軽量化・量子化生成回帰
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- Easy
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arxivPaper only2026-09-03
A hybrid pipeline for dynamic ontology-based semantic mapping
Semantic mapping plays a crucial role in the ability of a robot to interact with objects, operate and navigate
コンピュータビジョン物体検出検出回帰テキスト
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- 検出
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- Hard
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arxivPaper only2026-09-03
MINERVA: How Small Can a Manipulation Policy Be and Still Solve LIBERO?
Vision-language-action (VLA) models with billions of parameters now dominate the LIBERO manipulation benchmark
CPUで試しやすい深層学習軽量化・量子化回帰マルチモーダル
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arxivPaper only2026-09-02
A Closed-Form Formula for Consistent Lipschitz Regression on Metric Spaces with Sparse Neural Network Realizations
Several classical machine-learning methods, such as KRRs and SVRs, are both computationally and analytically t
深層学習Transformer回帰
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- Hard
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arxivPaper only2026-09-02
Momentum in large-batch training: Polyak enlarges the critical batch size, Nesterov improves data efficiency
We study when and how momentum improves large-batch training in the one-pass regime, using power-law kernel re
深層学習正規化・最適化手法回帰
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arxivPaper only2026-09-02
Bayes-Optimal BER and AUC: Estimation and Evaluation of Estimators
A fundamental quantity in machine learning is the optimal performance achievable by any model on a given task.
コンピュータビジョンセグメンテーション分類回帰
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- Hard
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arxivGitHubあり2026-09-02
Schrödinger Bridges on Lie Group Manifolds for Probabilistic Intrinsic Generation
Generative modeling directly on geometric manifolds can avoid errors introduced by flattening non-Euclidean da
コンピュータビジョンセグメンテーション生成回帰
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- Easy
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arxivPaper only2026-09-02
HyperMC: Multi-Fidelity Hyperparameter Tuning for Stochastic Gradient MCMC
Stochastic gradient Markov chain Monte Carlo (SGMCMC) methods enable scalable Bayesian inference, but their pe
深層学習Transformer生成回帰
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- Hard
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arxivPaper only2026-09-02
Pre-Lane-change Signal in Transitional Autonomous Vehicles: Results from Controlled Experiments
This paper investigates how a production transitional autonomous vehicle (tAV) develops and executes mandatory
自然言語処理RAG回帰
- 用途
- 回帰
- 難易度
- Hard
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arxivPaper only2026-09-01
Neural Symbollic Regression Using Deep Learning and Sparse Modelling
Symbolic Regression (SR) seeks to find succinct mathematical expressions that represent the fundamental relati
説明可能機械学習教師あり学習回帰異常検知
- 用途
- 回帰
- 難易度
- Hard
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arxivPaper only2026-08-31
Marginal Coordinate Test for Fréchet Regression with Random Objects
We develop a marginal coordinate test for regression with Euclidean predictors and a random-object response in
コンピュータビジョンセグメンテーション回帰半教師あり
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arxivPaper only2026-08-31
Flawed in Nature, Perfect through Evolution
The performance of artificial intelligence (AI) and machine learning (ML) models degrades when the problem the
深層学習軽量化・量子化生成回帰
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arxivPaper only2026-08-28
Learning between the peaks: sharp asymptotics for kernel ridge regression under power-law anisotropy
We study kernel ridge regression under anisotropic Gaussian data, where the input covariance decays as a power
コンピュータビジョンセグメンテーション回帰
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- Hard
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arxivPaper only2026-08-27
Fast Weight Attention for Continual Learning
Recurrent fast-weight memories and selective state-space models compress an expanding context into a fixed-siz
深層学習RNN / LSTM回帰テキスト
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- Hard
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arxivPaper only2026-08-27
Why not to use the Gaussian kernel
Kernels measure similarity or correlation in tasks such as regression and classification. The Gaussian kernel,
少数データ向き深層学習Transformer分類回帰
- 用途
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- 難易度
- Hard
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arxivPaper only2026-08-27
Hadamard Flattening and Gaussian Pooling Sketch for Least Squares with Coordinate-wise Guarantee
Randomized sketch-and-solve algorithms accelerate overconstrained $\ell_2$ regression by replacing the input w
深層学習正規化・最適化手法回帰
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arxivPaper only2026-08-26
Geometry-Constrained Kolmogorov-Arnold Networks: Learning Edge Geometry via Banach Duality
Kolmogorov-Arnold Networks (KANs) replace fixed activations in deep architectures with learnable univariate ed
説明可能自然言語処理RAG回帰
- 用途
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- 難易度
- Hard
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arxivPaper only2026-08-26
Multi-output Gaussian process prediction of physical fields under linear equality constraints
We address the simultaneous prediction of multiple high-dimensional physical fields governed by linear equalit
少数データ向き説明可能自然言語処理RAG回帰
- 用途
- 回帰
- 難易度
- Hard
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arxivPaper only2026-08-26
Fast rates in Bayesian online learning with approximate posteriors
Exact Bayes prediction enjoys fast predictive regret guarantees, but exact posterior updating or representatio
少数データ向きコンピュータビジョンセグメンテーション回帰
- 用途
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- Hard
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arxivPaper only2026-08-26
Adaptive Regularization for Random Features: A Neighboring Early-Stopping Rule with Oracle-Rate Guarantees
Random feature methods provide a scalable approximation to kernel ridge regression (KRR), but the regularizati
機械学習教師あり学習回帰
- 用途
- 回帰
- 難易度
- Hard
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arxivPaper only2026-08-26
Functional linear regression from sparse to dense designs: a pooling-ridge method and minimax optimality
Functional data analysis is an important statistical field that treats data as random functions. In practice,
コンピュータビジョンセグメンテーション回帰
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- Hard
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arxivPaper only2026-08-25
$\texttt{findr}$: Transparent and Fair Credit Risk Decisions through Semi-Structured Regressions
Credit risk models increasingly need to combine predictive accuracy with transparent explanations and auditabl
説明可能深層学習軽量化・量子化回帰テキスト
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- Hard
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arxivPaper only2026-08-25
Sequential operator learning under dependent data
Learning operators from sequentially collected data arises in adaptive experimental design, Bayesian optimizat
少数データ向きCPUで試しやすいセンサ/時系列条件最適化深層学習Transformer回帰
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- Hard
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arxivPaper only2026-08-25
Revenge of Monosemanticity: Specialized Neurons Improve Data Efficiency in MLPs
Understanding how neural networks learn and organize features is central to understanding their behavior. Much
生成AIGAN回帰
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- Hard
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arxivPaper only2026-08-25
Generalization, memorization, and overfitting for diffusion models trained in the lazy high-dimensional regime
Modern score-based generative models have achieved remarkable empirical success in high-dimensional tasks such
深層学習Transformer生成回帰画像
- 用途
- 生成
- 難易度
- Hard
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- High
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arxivPaper only2026-08-25
On Scaling Coordinate-Based Neuroevolution: The Quadtree Bottleneck in ES-HyperNEAT
ES-HyperNEAT evolves substrate topology through adaptive quadtree subdivision; to our knowledge, no implementa
CPUで試しやすいコンピュータビジョンセグメンテーション分類生成回帰
- 用途
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- 難易度
- Hard
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arxivPaper only2026-08-24
Interpretable AI with Local Distillation
Modern AI models such as tabular foundation models and gradient-boosted ensembles can outpredict classical met
表形式向き説明可能深層学習軽量化・量子化回帰表形式
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- 回帰
- 難易度
- Hard
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arxivPaper only2026-08-24
Stochastic gradient descent with initial regularization
We analyze a variant of stochastic gradient descent with initial regularization (SGDIR) and derive dimension-f
深層学習正規化・最適化手法回帰
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- Hard
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arxivPaper only2026-08-24
A Commutator Framework for Selective Spectral Alignment in Deep Neural Networks
We develop a finite-width geometric framework describing how learned feature geometries are organized, transpo
品質予測/異常検知深層学習Transformer回帰
- 用途
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- Hard
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arxivGitHubあり2026-08-24
JANUS: Online Jacobian-Aligned Infill for Black-Box Optimization
Population optimizers such as CMA-ES, DE, and multi-objective evolutionary algorithms drive search mainly thro
条件最適化自然言語処理ファインチューニング生成回帰テキスト
- 用途
- 生成
- 難易度
- Hard
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- High
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arxivPaper only2026-08-21
Free-Probability Kernels for Zero-Rollout Hyperparameter Selection in Reservoir Computing
Reservoir computing (RC) couples a fixed recurrent dynamical system with a trained lightweight readout, but th
少数データ向きCPUで試しやすい条件最適化深層学習Transformer回帰予測
- 用途
- 回帰
- 難易度
- Hard
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arxivPaper only2026-08-20
Enhanced Artificial Neural Networks Using QHAdamW in Air Quality Forecasting
The study employed an Artificial Neural Network in combination with the optimized Adaptive Moment Estimation (
品質予測/異常検知深層学習正規化・最適化手法回帰予測
- 用途
- 回帰
- 難易度
- Hard
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- High
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arxivPaper only2026-08-17
Automating Parent Selection Configuration in Genetic Programming with Agentic AI
We investigate whether agentic artificial intelligence can automate parts of the process of designing genetic
自然言語処理大規模言語モデル生成回帰テキスト
- 用途
- 生成
- 難易度
- Hard
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- High
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arxivPaper only2026-08-14
Adaptive Protection for Evolutionary Feature Construction in Symbolic Regression with Application to Credit Classification
Evolutionary feature construction has shown strong promise in symbolic regression by automatically discovering
説明可能品質予測/異常検知自然言語処理RAG分類回帰
- 用途
- 分類
- 難易度
- Hard
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arxivPaper only2026-07-31
Analysis of Memory-Runtime Trade-offs in Caching Strategies for Genetic Programming Symbolic Regression
Genetic Programming Symbolic Regression (GPSR) generates mathematical expressions to model input-output relati
深層学習軽量化・量子化回帰
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- Hard
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arxivPaper only2026-07-29
Shared Symbolic Backbones for Physically Consistent Multi-Output Symbolic Regression
Symbolic regression provides analytical expressions, but it is usually applied one output at a time. This is l
品質予測/異常検知自然言語処理RAG回帰
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arxivPaper only2026-07-29
Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks
回避可能な計算資源である雑音を扱い、学習と推論を行うための神経回路モデル(NNN)を提案。このモデルが学習し推論するための、伝達の反対方向の重みトランスポートの問題を回避できた。
深層学習正規化・最適化手法回帰
- 用途
- 人工神経回路のバックプロパゲーション復元
- 難易度
- Hard
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arxivPaper only2026-07-26
Benchmarking Zero-Shot LLM-Generated Parent Selection in Genetic Programming for Symbolic Regression
Parent selection significantly affects exploration, exploitation, and complexity control in genetic programmin
自然言語処理大規模言語モデル生成回帰テキスト
- 用途
- 生成
- 難易度
- Hard
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- High
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arxivPaper only2026-07-25
Continuous surrogates versus threshold Boolean networks for modeling Arabidopsis ISR gene regulation
Gene regulatory network modeling often requires balancing predictive accuracy and mechanistic interpretability
表形式向き説明可能CPUで試しやすい自然言語処理RAG回帰テキスト
- 用途
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- 難易度
- Hard
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arxivPaper only2026-07-22
Learning the Arabic Dialect Continuum as a Continuous Space: A Regression Approach to Speaker Origin Prediction
We present a regression-based approach to Arabic dialect geolocation that models dialectal variation as a cont
深層学習Transformer検出回帰
- 用途
- 検出
- 難易度
- Hard
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- High
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arxivPaper only2026-07-21
Spiking Neural Networks for fMRI-Based Visual Semantic Decoding
fMRIデータから視覚情報を解釈するために、スパイクニューラルネットワークを用いた方法を提案し、fMRIデータから視覚情報を解釈する検証を行う。
深層学習Transformer回帰画像
- 用途
- fMRIから視覚情報の解釈
- 難易度
- Hard
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- Medium
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