yusuke1997/dblp-id-title huggingface dataset:
Shadowing Properties of Optimization Algorithms
Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions
Fast Randomized Kernel Ridge Regression with Statistical Guarantees
Nonparametric Evaluation of Noisy ICA Solutions
Sparse Hypergraph Community Detection Thresholds in Stochastic Block Model
Data center cooling using model-predictive control
Learning Transferable Features for Point Cloud Detection via 3D Contrastive Co-training
Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature
Neural Anisotropy Directions
Learning Image Descriptors with the Boosting-Trick
Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys
Maximum Causal Tsallis Entropy Imitation Learning
Recognizing Evoked Potentials in a Virtual Environment
Random Projection Trees Revisited
Quantifying how much sensory information in a neural code is relevant for behavior
A Non-commutative Extension of Lee-Seung's Algorithm for Positive Semidefinite Factorizations
Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity
Learning from Pattern Completion: Self-supervised Controllable Generation
Masked Autoregressive Flow for Density Estimation
Graphical Models for Inference with Missing Data
Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision
On Feature Learning in Structured State Space Models
Stabilizing Training of Generative Adversarial Networks through Regularization
Towards Faster Stochastic Gradient Search
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
Self-Supervised Learning Disentangled Group Representation as Feature
How Powerful are K-hop Message Passing Graph Neural Networks
Practical Quasi-Newton Methods for Training Deep Neural Networks
Automatic Data Augmentation for Generalization in Reinforcement Learning
VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web
SurDis: A Surface Discontinuity Dataset for Wearable Technology to Assist Blind Navigation in Urban Environments
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography
Modeling the Olfactory Bulb - Coupled Nonlinear Oscillators
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity
CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence
Bounding Performance Loss in Approximate MDP Homomorphisms
The Brain Uses Reliability of Stimulus Information when Making Perceptual Decisions
A Residual Bootstrap for High-Dimensional Regression with Near Low-Rank Designs
Statistical Efficiency of Distributional Temporal Difference Learning
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
Most Influential Subset Selection: Challenges, Promises, and Beyond
Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset
Semantic HELM: A Human-Readable Memory for Reinforcement Learning
Weighted Likelihood Policy Search with Model Selection
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm
Mirror Diffusion Models for Constrained and Watermarked Generation
An effective framework for estimating individualized treatment rules
A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning
EDGI: Equivariant Diffusion for Planning with Embodied Agents
3D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization
Learning Theory and Experiments with Competitive Networks
Online Algorithms for the Santa Claus Problem
Multilabel reductions: what is my loss optimising?
PGDiff: Guiding Diffusion Models for Versatile Face Restoration via Partial Guidance
How Does Message Passing Improve Collaborative Filtering?
High Probability Complexity Bounds for Line Search Based on Stochastic Oracles
Scaling the Codebook Size of VQ-GAN to 100, 000 with a Utilization Rate of 99%
RAFT: A Real-World Few-Shot Text Classification Benchmark
Consistent optimization of AMS by logistic loss minimization
Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification
Elliptical Attention
Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods
ANT: Adaptive Noise Schedule for Time Series Diffusion Models
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games
Exploiting the Surrogate Gap in Online Multiclass Classification
Active Learning by Querying Informative and Representative Examples
CoSy: Evaluating Textual Explanations of Neurons
Regularizing Black-box Models for Improved Interpretability
A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective
Characterizing Neurons in the Primary Auditory Cortex of the Awake Primate Using Reverse Correlation
Parameterized Knowledge Transfer for Personalized Federated Learning
AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Models
Truly Scale-Equivariant Deep Nets with Fourier Layers
Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control
Practical Hash Functions for Similarity Estimation and Dimensionality Reduction
BEACON: Benchmark for Comprehensive RNA Tasks and Language Models
Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies
Interior Point Solving for LP-based prediction+optimisation
What Would Jiminy Cricket Do? Towards Agents That Behave Morally
ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fields
Neuron Merging: Compensating for Pruned Neurons
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
Behavior Transformers: Cloning $k$ modes with one stone
Multiclass versus Binary Differentially Private PAC Learning
Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities
Learning a Color Algorithm from Examples
Efficient Learning of Discrete-Continuous Computation Graphs
Learning Representations via a Robust Behavioral Metric for Deep Reinforcement Learning
StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses
Noisy Recurrent Neural Networks
Divisive Normalization, Line Attractor Networks and Ideal Observers
DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning
Generalization bounds for neural ordinary differential equations and deep residual networks
Active, anytime-valid risk controlling prediction sets
MAP estimation in Binary MRFs via Bipartite Multi-cuts
Gene-Gene Relationship Modeling Based on Genetic Evidence for Single-Cell RNA-Seq Data Imputation
Panacea: Pareto Alignment via Preference Adaptation for LLMs
A Model of Neural Oscillator for a Unified Submodule
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
Predicting Speech Intelligibility from a Population of Neurons
Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than O(1/\epsilon)
Interpolating between types and tokens by estimating power-law generators
Semi-Automated Data Labeling
Temporal-attentive Covariance Pooling Networks for Video Recognition
Towards More Practical Adversarial Attacks on Graph Neural Networks
Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning
Exploring the Latent Space of Autoencoders with Interventional Assays
Delay Compensation with Dynamical Synapses
Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation
Hybrid Circuits of Interacting Computer Model and Biological Neurons
Structured Embedding Models for Grouped Data
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs
RelaySum for Decentralized Deep Learning on Heterogeneous Data
Extracting Dynamical Structure Embedded in Neural Activity
Blending Autonomous Exploration and Apprenticeship Learning
ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery
Learning Chordal Markov Networks by Dynamic Programming
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis
Learning Disentangled Representations and Group Structure of Dynamical Environments
A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
Diverse Ensemble Evolution: Curriculum Data-Model Marriage
VoiceMixer: Adversarial Voice Style Mixup
Feature Clustering for Accelerating Parallel Coordinate Descent
MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators
Sparse DNNs with Improved Adversarial Robustness
Proximal Causal Inference With Text Data
Variational inference via Wasserstein gradient flows
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back
Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust
Improving the Accuracy and Speed of Support Vector Machines
Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision
Data Cleansing for Models Trained with SGD
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation
DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection
Adaptive Layer Sparsity for Large Language Models via Activation Correlation Assessment
Adversarial Examples Make Strong Poisons
Learning Mixed Multinomial Logits with Provable Guarantees
DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph
Model-Based Opponent Modeling
Self-supervised Graph Neural Networks via Low-Rank Decomposition
CrossTransformers: spatially-aware few-shot transfer
A Theory of PAC Learnability under Transformation Invariances
Nonparametric Multi-group Membership Model for Dynamic Networks
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks
Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy
How to Boost Any Loss Function
Learning Physical Graph Representations from Visual Scenes
On the training dynamics of deep networks with $L_2$ regularization
SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding
Incorporating BERT into Parallel Sequence Decoding with Adapters
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
Agnostic Estimation for Misspecified Phase Retrieval Models
Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold
ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors
Causal Abstractions of Neural Networks
Society of Agents: Regret Bounds of Concurrent Thompson Sampling
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression
Neural FFTs for Universal Texture Image Synthesis
Identifying Distributed Object Representations in Human Extrastriate Visual Cortex
First-Order Minimax Bilevel Optimization
A Topology-aware Graph Coarsening Framework for Continual Graph Learning
Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection
Self-explaining deep models with logic rule reasoning
Learning semantic similarity in a continuous space
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization
Zipper: Addressing Degeneracy in Algorithm-Agnostic Inference
Enabling hyperparameter optimization in sequential autoencoders for spiking neural data
Label-invariant Augmentation for Semi-Supervised Graph Classification
Towards Automatic Concept-based Explanations
High-Throughput Synchronous Deep RL
TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis
Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets
NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations
Efficient Active Learning for Gaussian Process Classification by Error Reduction
SMYRF - Efficient Attention using Asymmetric Clustering
MORA: Improving Ensemble Robustness Evaluation with Model Reweighing Attack
BOLD: Boolean Logic Deep Learning
Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations
Perceptual Metamers in Stereoscopic Vision
Dissecting Query-Key Interaction in Vision Transformers
Noise-Enhanced Associative Memories
CoinPress: Practical Private Mean and Covariance Estimation
Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields
Self-Consistent Models and Values
Deep Ensembles Work, But Are They Necessary?
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding
VSM: A Versatile Semi-supervised Model for Multi-modal Cell Instance Segmentation
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling
Can Graph Learning Improve Planning in LLM-based Agents?
Coresets for Scalable Bayesian Logistic Regression
A Neural Model of Descending Gain Control in the Electrosensory System
Sequence-to-Set Generative Models
The Gyro-Structure of Some Matrix Manifolds
Depth Uncertainty in Neural Networks
Validating Climate Models with Spherical Convolutional Wasserstein Distance
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite-Quadratic-Linear Programming
Multi-fidelity Monte Carlo: a pseudo-marginal approach
Compressed Least-Squares Regression
Learning with little mixing
Strategic Apple Tasting
Estimating vector fields using sparse basis field expansions
Practical Contextual Bandits with Feedback Graphs
Consistent feature selection for analytic deep neural networks
Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI
Representation Balancing MDPs for Off-policy Policy Evaluation
On the Non-Existence of a Universal Learning Algorithm for Recurrent Neural Networks
OKRidge: Scalable Optimal k-Sparse Ridge Regression
Probably Approximately Correct Constrained Learning
Asynchronous Decentralized SGD with Quantized and Local Updates
On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling
Clustering Stable Instances of Euclidean k-means
Efficient Learning of Linear Graph Neural Networks via Node Subsampling
Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networks
LLM-Pruner: On the Structural Pruning of Large Language Models
Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions
Computer Modeling of Associative Learning
Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test
Training Deep Networks without Learning Rates Through Coin Betting
From MAP to Marginals: Variational Inference in Bayesian Submodular Models
CLIP in Mirror: Disentangling text from visual images through reflection
Reconciling Competing Sampling Strategies of Network Embedding
A State-Space Model for Decoding Auditory Attentional Modulation from MEG in a Competing-Speaker Environment
SustainDC: Benchmarking for Sustainable Data Center Control
Transformers from an Optimization Perspective
The emergence of multiple retinal cell types through efficient coding of natural movies
Evaluation of Rarity of Fingerprints in Forensics
Continual Learning of Control Primitives : Skill Discovery via Reset-Games
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
BooVI: Provably Efficient Bootstrapped Value Iteration
Learning Temporal Point Processes via Reinforcement Learning
Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions
Ordinal Regression by Extended Binary Classification
Approximate Inference by Compilation to Arithmetic Circuits
FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning
Generate Universal Adversarial Perturbations for Few-Shot Learning
Further Explorations in Visually-Guided Reaching: Making MURPHY Smarter
Information Bottleneck for Non Co-Occurrence Data
Alignment at Pre-training! Towards Native Alignment for Arabic LLMs
Error Analysis of Generalized Nyström Kernel Regression
Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex
Combinatorial Bandits with Linear Constraints: Beyond Knapsacks and Fairness
Tree-to-tree Neural Networks for Program Translation
Localized Symbolic Knowledge Distillation for Visual Commonsense Models
Counting Distinct Elements Under Person-Level Differential Privacy
Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds
Self Organizing Neural Networks for the Identification Problem
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
Approximate inference in continuous time Gaussian-Jump processes
Structured Neural Networks for Density Estimation and Causal Inference
Debiasing Synthetic Data Generated by Deep Generative Models
Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors
Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork
General-Purpose Localization of Textured Image Regions
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes
The Perturbed Variation
Factorized Neural Processes for Neural Processes: K-Shot Prediction of Neural Responses
Generative modeling for protein structures
Binary Coding in Auditory Cortex
Fast and accurate spike sorting of high-channel count probes with KiloSort
Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting
FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation
Challenges and Opportunities in High Dimensional Variational Inference
VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering
Tanh Works Better with Asymmetry
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
Quantile Propagation for Wasserstein-Approximate Gaussian Processes
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms
Global-aware Beam Search for Neural Abstractive Summarization
Meta Learning Backpropagation And Improving It
QMDP-Net: Deep Learning for Planning under Partial Observability
Dataset Distillation with Infinitely Wide Convolutional Networks
A Denoising View of Matrix Completion
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features
Fine-grained Optimization of Deep Neural Networks
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning
Adaptation to Easy Data in Prediction with Limited Advice
Densely Connected Attention Propagation for Reading Comprehension
Neural Algorithmic Reasoning Without Intermediate Supervision
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation
Vocal Call Locator Benchmark (VCL) for localizing rodent vocalizations from multi-channel audio
Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis
Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
Instance-Optimal Private Density Estimation in the Wasserstein Distance
Learning Deep Parsimonious Representations
Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation
NeuroScale: Novel Topographic Feature Extraction using RBF Networks
Concentration of risk measures: A Wasserstein distance approach
Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block Models
BendVLM: Test-Time Debiasing of Vision-Language Embeddings
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Discovering Intrinsic Spatial-Temporal Logic Rules to Explain Human Actions
Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition
OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
Exploration in Structured Reinforcement Learning
Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks
Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech
Joint Inference for Neural Network Depth and Dropout Regularization
Fast Approximate Dynamic Programming for Infinite-Horizon Markov Decision Processes
Differentiable hierarchical and surrogate gradient search for spiking neural networks
A Deep Reinforcement Learning Framework for Column Generation
Testing for Families of Distributions via the Fourier Transform
A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++
Continuously-adaptive discretization for message-passing algorithms
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning
Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks
Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games
Learning from Label Proportions by Learning with Label Noise
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning
Learning Functional Transduction
Regularized Policy Iteration
Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies
Latent Neural Operator for Solving Forward and Inverse PDE Problems
Optimal Algorithms for Augmented Testing of Discrete Distributions
ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints
Computer Recognition of Wave Location in Graphical Data by a Neural Network
ProgressGym: Alignment with a Millennium of Moral Progress
OV-PARTS: Towards Open-Vocabulary Part Segmentation
Magnitude-sensitive preference formation
Active Learning in the Drug Discovery Process
DNA 2 DNA Computation: A Potential Killer Application?
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching
Distributed k-means and k-median clustering on general communication topologies
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance
Private Everlasting Prediction