yusuke1997/dblp-id-title huggingface dataset:
Low-dimensional Structure in the Space of Language Representations is Reflected in Brain Responses
Sample complexity and effective dimension for regression on manifolds
Chaotic Dynamics are Intrinsic to Neural Network Training with SGD
InversionView: A General-Purpose Method for Reading Information from Neural Activations
Better Transfer Learning with Inferred Successor Maps
Counterfactual Vision-and-Language Navigation: Unravelling the Unseen
Characterizing neural dependencies with copula models
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN
Monomial Matrix Group Equivariant Neural Functional Networks
INRAS: Implicit Neural Representation for Audio Scenes
Contextual Combinatorial Multi-armed Bandits with Volatile Arms and Submodular Reward
Comparing Bayesian models for multisensory cue combination without mandatory integration
Workshop on High-energy Physics and Machine Learning, HEPML 2014, held at NIPS 2014, Montreal, Quebec, Canada, December 8-13, 2014
Online Variational Approximations to non-Exponential Family Change Point Models: With Application to Radar Tracking
A Digital Antennal Lobe for Pattern Equalization: Analysis and Design
Construction of Nonparametric Bayesian Models from Parametric Bayes Equations
Catching Change-points with Lasso
Neural Networks with Quadratic VC Dimension
Learning Low-Rank Feature for Thorax Disease Classification
Linear-time inference in Hierarchical HMMs
RED : Looking for Redundancies for Data-FreeStructured Compression of Deep Neural Networks
Exactly Computing the Local Lipschitz Constant of ReLU Networks
Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement
Robust Graph Neural Networks via Unbiased Aggregation
Efficient Online Learning via Randomized Rounding
MBW: Multi-view Bootstrapping in the Wild
Learning with Holographic Reduced Representations
Neuro-Symbolic Data Generation for Math Reasoning
Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks
Causal Discovery from Discrete Data using Hidden Compact Representation
Learning low-dimensional state embeddings and metastable clusters from time series data
Analysis of Contour Motions
Separate and Reconstruct: Asymmetric Encoder-Decoder for Speech Separation
On the generalization of learning algorithms that do not converge
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual Classification
Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting
Deep ReLU Networks Have Surprisingly Few Activation Patterns
Diverse Community Data for Benchmarking Data Privacy Algorithms
Exploiting hidden structures in non-convex games for convergence to Nash equilibrium
On Causal Discovery with Cyclic Additive Noise Models
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
Learning to Ground Multi-Agent Communication with Autoencoders
Revisiting Ensembling in One-Shot Federated Learning
Information, Prediction, and Query by Committee
The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities
A Smoothed Approximate Linear Program
NeuroEvoBench: Benchmarking Evolutionary Optimizers for Deep Learning Applications
Linear Disentangled Representations and Unsupervised Action Estimation
Stochastic Variational Deep Kernel Learning
End-to-end Symbolic Regression with Transformers
Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach
On Gap-dependent Bounds for Offline Reinforcement Learning
Handling Advertisements of Unknown Quality in Search Advertising
Unlabeled Principal Component Analysis
Adaptivity to Local Smoothness and Dimension in Kernel Regression
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems
IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI
Cocktail: Mixing Multi-Modality Control for Text-Conditional Image Generation
ACh, Uncertainty, and Cortical Inference
Pareto Set Learning for Expensive Multi-Objective Optimization
Orthogonal Non-negative Tensor Factorization based Multi-view Clustering
Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer
Spectral Regularization for Support Estimation
On Margin-Based Cluster Recovery with Oracle Queries
Fighting Boredom in Recommender Systems with Linear Reinforcement Learning
Inverting Gradients - How easy is it to break privacy in federated learning?
OnlineTAS: An Online Baseline for Temporal Action Segmentation
Sequential Information Design: Learning to Persuade in the Dark
Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates
DALD: Improving Logits-based Detector without Logits from Black-box LLMs
OmniPrint: A Configurable Printed Character Synthesizer
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-resolution and Beyond
Rate-Agnostic (Causal) Structure Learning
Multi-Agent Generative Adversarial Imitation Learning
Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses
Graph Learning Assisted Multi-Objective Integer Programming
Adaptive Martingale Boosting
The Functional Neural Process
Learning Best Combination for Efficient N: M Sparsity
Dynamic, Non-Local Role Bindings and Inferencing in a Localist Network for Natural Language Understanding
DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification
Challenges of Generating Structurally Diverse Graphs
A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection
Minimum norm interpolation by perceptra: Explicit regularization and implicit bias
MiSO: Optimizing brain stimulation to create neural activity states
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data
EgoDistill: Egocentric Head Motion Distillation for Efficient Video Understanding
EZ-HOI: VLM Adaptation via Guided Prompt Learning for Zero-Shot HOI Detection
Modality-Agnostic Topology Aware Localization
Efficient Algorithms for Device Placement of DNN Graph Operators
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning
Learning curves for multi-task Gaussian process regression
Duality, Geometry, and Support Vector Regression
Graph Contrastive Learning with Augmentations
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
Zero-Sum Stochastic Stackelberg Games
Sparse Learning with CART
Implicit Convolutional Kernels for Steerable CNNs
Improving Human Judgments by Decontaminating Sequential Dependencies
Assumption violations in causal discovery and the robustness of score matching
Fully Sparse 3D Object Detection
Learning Graph Structure With A Finite-State Automaton Layer
From Bandits to Experts: On the Value of Side-Observations
Most ReLU Networks Suffer from $\ell^2$ Adversarial Perturbations
The Impact of Regularization on High-dimensional Logistic Regression
Learning Concept Credible Models for Mitigating Shortcuts
An Oblique Approach to Prediction of Conversion to Alzheimer's Disease with Multikernel Gaussian Processes
Learning Physical Constraints with Neural Projections
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning
LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing
Multilabel Classification using Bayesian Compressed Sensing
AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control
Dirichlet-Enhanced Spam Filtering based on Biased Samples
Universal Rates for Active Learning
Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime
Safe Pontryagin Differentiable Programming
Neural Network Weight Matrix Synthesis Using Optimal Control Techniques
Compression with Bayesian Implicit Neural Representations
Revealing the unseen: Benchmarking video action recognition under occlusion
On the Complexity of Identification in Linear Structural Causal Models
A Recurrent Model of Orientation Maps with Simple and Complex Cells
An Autoencoder-Like Nonnegative Matrix Co-Factorization for Improved Student Cognitive Modeling
MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control
On the Computational Landscape of Replicable Learning
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification
Scalar Posterior Sampling with Applications
Identification of OCD-Relevant Brain Areas through Multivariate Feature Selection
Invariance-Aware Randomized Smoothing Certificates
How a Student becomes a Teacher: learning and forgetting through Spectral methods
Top Two Algorithms Revisited
Why Neuronal Dynamics Should Control Synaptic Learning Rules
Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation
mRI: Multi-modal 3D Human Pose Estimation Dataset using mmWave, RGB-D, and Inertial Sensors
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
RMLR: Extending Multinomial Logistic Regression into General Geometries
Matryoshka Query Transformer for Large Vision-Language Models
Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model
Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles
Post-Contextual-Bandit Inference
A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Bayesian Active Model Selection with an Application to Automated Audiometry
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions
Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration
Active Learning for Semantic Segmentation with Multi-class Label Query
Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
Unified Language Model Pre-training for Natural Language Understanding and Generation
Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems
The Tempo 2 Algorithm: Adjusting Time-Delays By Supervised Learning
Three Towers: Flexible Contrastive Learning with Pretrained Image Models
Sparse deep belief net model for visual area V2
Scalable Inference of Sparsely-changing Gaussian Markov Random Fields
Capacity of strong attractor patterns to model behavioural and cognitive prototypes
FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving
The Boltzmann Perceptron Network: A Multi-Layered Feed-Forward Network Equivalent to the Boltzmann Machine
On Training Implicit Models
Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
Online and Offline Reinforcement Learning by Planning with a Learned Model
Learning with Group Invariant Features: A Kernel Perspective
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules
Universal models for binary spike patterns using centered Dirichlet processes
Fast Distributed k-Center Clustering with Outliers on Massive Data
Use-Case-Grounded Simulations for Explanation Evaluation
Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations
Online Learning with Transductive Regret
AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games
Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks
Scalable Graph Neural Networks via Bidirectional Propagation
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
Extensions of Generalized Binary Search to Group Identification and Exponential Costs
Doubly Robust Counterfactual Classification
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses
Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships
BooVAE: Boosting Approach for Continual Learning of VAE
Automatic Discovery of Cognitive Skills to Improve the Prediction of Student Learning
Dueling over Dessert, Mastering the Art of Repeated Cake Cutting
Adversarial Text Generation via Feature-Mover's Distance
Graph Convolutional Kernel Machine versus Graph Convolutional Networks
CLIP-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments
Strategic Classification under Unknown Personalized Manipulation
Reducing statistical dependencies in natural signals using radial Gaussianization
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
What is being transferred in transfer learning?
The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces
3D Shape Reconstruction from Vision and Touch
Interventional Few-Shot Learning
Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay
Augmented Memory Replay-based Continual Learning Approaches for Network Intrusion Detection
The Capacity of a Bump
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective
Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach
Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests
Learning from Rich Semantics and Coarse Locations for Long-tailed Object Detection
DiffuLT: Diffusion for Long-tail Recognition Without External Knowledge
PAC-Bayes Un-Expected Bernstein Inequality
Active Bayesian Causal Inference
Improving Neural ODE Training with Temporal Adaptive Batch Normalization
Preference-based Reinforcement Learning with Finite-Time Guarantees
Optimistic optimization of a Brownian
Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression
Regularized Learning with Networks of Features
RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
Learning Manifold Dimensions with Conditional Variational Autoencoders
LLMDFA: Analyzing Dataflow in Code with Large Language Models
Multi-resolution Exploration in Continuous Spaces
Streaming k-means approximation
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
Chain of Reasoning for Visual Question Answering
Rule Representations in a Connectionist Chunker
Semantic Routing via Autoregressive Modeling
Simple and Fast Algorithm for Binary Integer and Online Linear Programming
Multitask learning meets tensor factorization: task imputation via convex optimization
Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines
Probabilistic Time Series Forecasting with Shape and Temporal Diversity
AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queries
Sparse and Smooth Adjustments for Coherent Forecasts in Temporal Aggregation of Time Series
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup
Geometric Trajectory Diffusion Models
Large Scale Online Learning
BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval
Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs
Adversarial Environment Design via Regret-Guided Diffusion Models
b-bit Marginal Regression
Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs
On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations
Position-based Multiple-play Bandit Problem with Unknown Position Bias
Data-Informed Geometric Space Selection
Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms
Reconstructing Training Data From Trained Neural Networks
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret
Scaling Riemannian Diffusion Models
Logistic Regression for Single Trial EEG Classification
Co-teaching: Robust training of deep neural networks with extremely noisy labels
The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation
Tight Sample Complexity of Learning One-hidden-layer Convolutional Neural Networks
Regulating algorithmic filtering on social media
Exploring Unknown Environments with Real-Time Search or Reinforcement Learning
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models
Learning Erdos-Renyi Random Graphs via Edge Detecting Queries
Asynchronous Parallel Greedy Coordinate Descent
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos
Learning to See by Looking at Noise
Neural representation of action sequences: how far can a simple snippet-matching model take us?
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization
Online Learning from Finite Training Sets: An Analytical Case Study
Learning threshold neurons via edge of stability
Large Language Models' Expert-level Global History Knowledge Benchmark (HiST-LLM)
Causal Bandits with Unknown Graph Structure
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Counterfactually Fair Representation
Neural Surface Reconstruction of Dynamic Scenes with Monocular RGB-D Camera
Should We Really Edit Language Models? On the Evaluation of Edited Language Models
HumanVLA: Towards Vision-Language Directed Object Rearrangement by Physical Humanoid
Psychiatry: Insights into depression through normative decision-making models
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
Generalizing GANs: A Turing Perspective
Counterfactually Comparing Abstaining Classifiers
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence
Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity
On the Sample Complexity of Robust PCA
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning
Exploiting weakly supervised visual patterns to learn from partial annotations
Auditing Privacy Mechanisms via Label Inference Attacks
Memory-based Stochastic Optimization
CoLLAT: On Adding Fine-grained Audio Understanding to Language Models using Token-Level Locked-Language Tuning
Near-Minimax Optimal Classification with Dyadic Classification Trees
On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples
Dimension-Free Bounds for Low-Precision Training
Learning Identifiable Factorized Causal Representations of Cellular Responses
Characterizing Optimal Mixed Policies: Where to Intervene and What to Observe
Greedy Model Averaging
Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games
Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
Modeling human function learning with Gaussian processes
Online Dynamic Programming
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections
Curriculum By Smoothing
Fast rates for prediction with limited expert advice
Mini-Sequence Transformers: Optimizing Intermediate Memory for Long Sequences Training
Active Exploration in Dynamic Environments
Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts
Super Consistency of Neural Network Landscapes and Learning Rate Transfer
Provably Safe Neural Network Controllers via Differential Dynamic Logic
Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation
Delving into Sequential Patches for Deepfake Detection
An Orientation Selective Neural Network for Pattern Identification in Particle Detectors
Adaptive Exploration for Data-Efficient General Value Function Evaluations
CALVIN: Improved Contextual Video Captioning via Instruction Tuning
Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign?
Multi-domain Causal Structure Learning in Linear Systems
WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates
Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting
Hyperbolic Busemann Learning with Ideal Prototypes
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
Least Squares Regression Can Exhibit Under-Parameterized Double Descent
A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
A More Powerful Two-Sample Test in High Dimensions using Random Projection
Towards a theory of how the structure of language is acquired by deep neural networks
Learning Predictions for Algorithms with Predictions
SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction
Everyday Object Meets Vision-and-Language Navigation Agent via Backdoor
Selecting Observations against Adversarial Objectives
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials
Using Random Forests in the Structured Language Model
Tensor Wheel Decomposition and Its Tensor Completion Application
URLB: Unsupervised Reinforcement Learning Benchmark
Are Large Language Models Good Statisticians?
Q-Clustering
DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction
Logarithmic Regret in Feature-based Dynamic Pricing
Revisiting Injective Attacks on Recommender Systems
Few-shot Video-to-Video Synthesis
PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction
A Method for the Design of Stable Lateral Inhibition Networks that is Robust in the Presence of Circuit Parasitics
On the accuracy of l1-filtering of signals with block-sparse structure
Few-shot Image Generation with Elastic Weight Consolidation
CoNT: Contrastive Neural Text Generation
Inherent Weight Normalization in Stochastic Neural Networks
Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation
Demixed Principal Component Analysis
Variational Denoising Network: Toward Blind Noise Modeling and Removal
Transfer Learning in a Transductive Setting
Quadrature-based features for kernel approximation
Average Case Column Subset Selection for Entrywise 퓁 1 -Norm Loss
RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models
APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction
A Rotation and Translation Invariant Discrete Saliency Network
Markov Random Fields Can Bridge Levels of Abstraction
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models
DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarios