yusuke1997/dblp-id-title huggingface dataset:
Fair Algorithms for Clustering
PSD Representations for Effective Probability Models
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies
EDT: An Efficient Diffusion Transformer Framework Inspired by Human-like Sketching
STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data
LGDN: Language-Guided Denoising Network for Video-Language Modeling
A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation
CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training
Deep Poisson gamma dynamical systems
An implicit function learning approach for parametric modal regression
Stochastic Submodular Maximization: The Case of Coverage Functions
Meta-Learning with Neural Bandit Scheduler
Statistical Inference for Pairwise Graphical Models Using Score Matching
Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation
3D Siamese Voxel-to-BEV Tracker for Sparse Point Clouds
Interpretable Image Classification with Adaptive Prototype-based Vision Transformers
ResQ: A Residual Q Function-based Approach for Multi-Agent Reinforcement Learning Value Factorization
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards
Information-constrained optimization: can adaptive processing of gradients help?
Effects of Data Geometry in Early Deep Learning
ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
Effective Exploration Based on the Structural Information Principles
Implicit Generative Copulas
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation
Disentangling by Subspace Diffusion
Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]
AdaPlanner: Adaptive Planning from Feedback with Language Models
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning
Adaptive Online Replanning with Diffusion Models
A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers
The Generalisation Cost of RAMnets
Kernels for gene regulatory regions
Evolution-Guided Policy Gradient in Reinforcement Learning
Safe Exploitative Play with Untrusted Type Beliefs
Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers
Mirror Langevin Monte Carlo: the Case Under Isoperimetry
Rethinking gradient sparsification as total error minimization
A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation
Cross-model Control: Improving Multiple Large Language Models in One-time Training
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition
JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images
Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging
Learning to Learn By Self-Critique
Harmonizing the object recognition strategies of deep neural networks with humans
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
FedSR: A Simple and Effective Domain Generalization Method for Federated Learning
Bootstrapping Vision-Language Learning with Decoupled Language Pre-training
Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing
Insights on representational similarity in neural networks with canonical correlation
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning
Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction
488 Solutions to the XOR Problem
SegViT: Semantic Segmentation with Plain Vision Transformers
Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator
Fast Transformers with Clustered Attention
Learning Bounds for Risk-sensitive Learning
Consistency-based Semi-supervised Learning for Object detection
Self-Organization of Associative Database and Its Applications
From Data Distributions to Regularization in Invariant Learning
Efficient characterization of electrically evoked responses for neural interfaces
Reward is enough for convex MDPs
HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
Learning sparse features can lead to overfitting in neural networks
Scalable Coordinated Exploration in Concurrent Reinforcement Learning
RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning Attacks
Expectation Maximization and Posterior Constraints
Navigating Chemical Space with Latent Flows
Large Language Model Unlearning
Implicit Manifold Gaussian Process Regression
Implicit Contrastive Representation Learning with Guided Stop-gradient
A Humanlike Predictor of Facial Attractiveness
Fast Non-Linear Dimension Reduction
Multistage Campaigning in Social Networks
One sketch for all: Theory and Application of Conditional Random Sampling
Retrieval-Augmented Diffusion Models for Time Series Forecasting
Experience Replay for Continual Learning
Topological Parallax: A Geometric Specification for Deep Perception Models
TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion
Modeling Temporal Structure in Classical Conditioning
"On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking"
Misspecified Gaussian Process Bandit Optimization
Conformal Prediction Under Covariate Shift
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences
Constrained Langevin Algorithms with L-mixing External Random Variables
How Transferable are Video Representations Based on Synthetic Data?
Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions
Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning
Information-guided Planning: An Online Approach for Partially Observable Problems
Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning
Tiled convolutional neural networks
Large Margin Discriminant Dimensionality Reduction in Prediction Space
Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness
Matching the Statistical Query Lower Bound for k-Sparse Parity Problems with Sign Stochastic Gradient Descent
Clockwork Variational Autoencoders
Regularized estimation of image statistics by Score Matching
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
Multi-Task Learning as Multi-Objective Optimization
Object Recognition by Scene Alignment
Learning Multiple Markov Chains via Adaptive Allocation
Estimating image bases for visual image reconstruction from human brain activity
Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space
Learning Graphical Models with Mercer Kernels
Is Multiple Object Tracking a Matter of Specialization?
Coresets for Relational Data and The Applications
Learning Human-like Knowledge by Singular Value Decomposition: A Progress Report
Invertible Monotone Operators for Normalizing Flows
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
Curvilinear Distance Metric Learning
Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget
Redistribution of Weights and Activations for AdderNet Quantization
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
Distributed Distributionally Robust Optimization with Non-Convex Objectives
Provable Benefits of Complex Parameterizations for Structured State Space Models
MarioGPT: Open-Ended Text2Level Generation through Large Language Models
The alignment property of SGD noise and how it helps select flat minima: A stability analysis
Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture
Escaping Saddle Points in Constrained Optimization
Clusters and Coarse Partitions in LP Relaxations
Deflation Methods for Sparse PCA
Label Selection on Graphs
KS-GNN: Keywords Search over Incomplete Graphs via Graphs Neural Network
Mining GOLD Samples for Conditional GANs
The non-convex Burer-Monteiro approach works on smooth semidefinite programs
Cross-modal Learning for Image-Guided Point Cloud Shape Completion
PRANK: motion Prediction based on RANKing
Multiple Instance Filtering
Contextual Multinomial Logit Bandits with General Value Functions
On the Hardness of Robust Classification
Perception Test: A Diagnostic Benchmark for Multimodal Video Models
Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation
Task-based End-to-end Model Learning in Stochastic Optimization
RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations
On the Estimation Bias in Double Q-Learning
Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting
Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models
A teacher-teacher framework for clinical language representation learning
Few-Shot Object Detection via Association and DIscrimination
Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors
Phasor Neural Networks
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
Horizon-Independent Minimax Linear Regression
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Bayesian Alignments of Warped Multi-Output Gaussian Processes
Matching Free Trees with Replicator Equations
Online Consistency of the Nearest Neighbor Rule
Acceleration through Optimistic No-Regret Dynamics
A Walsh Hadamard Derived Linear Vector Symbolic Architecture
Calibrating "Cheap Signals" in Peer Review without a Prior
Going Metric: Denoising Pairwise Data
3D Social Saliency from Head-mounted Cameras
Optimal Hypothesis Selection in (Almost) Linear Time
Off-Policy Evaluation and Learning for External Validity under a Covariate Shift
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization
Decoding Ipsilateral Finger Movements from ECoG Signals in Humans
Average-case hardness of RIP certification
Approximately Equivariant Graph Networks
Geometry-Aware Recurrent Neural Networks for Active Visual Recognition
Top-Down and Bottom-Up Interactions between Low-Level Reactive Control and Symbolic Rule Learning in Embodied Agents
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
SNAKE: Shape-aware Neural 3D Keypoint Field
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation
TransformerFusion: Monocular RGB Scene Reconstruction using Transformers
On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks
A Variational Approach for Learning from Positive and Unlabeled Data
Modeling Neuronal Interactivity using Dynamic Bayesian Networks
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Solving graph compression via optimal transport
Multivariate Regression with Calibration
Are All Losses Created Equal: A Neural Collapse Perspective
BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text
Dynamic Learning in Large Matching Markets
BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages
Regularized Weighted Low Rank Approximation
A Self-Organizing Integrated Segmentation and Recognition Neural Net
Real-time data analysis at the LHC: present and future
Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data
Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs
Policy Improvement using Language Feedback Models
Pre-training via Paraphrasing
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
Prediction of Beta Sheets in Proteins
Mixture of Scales: Memory-Efficient Token-Adaptive Binarization for Large Language Models
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
An aVLSI Cricket Ear Model
Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems
Neural Word Embedding as Implicit Matrix Factorization
Synergistic Dual Spatial-aware Generation of Image-to-text and Text-to-image
Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning
Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments
Toward Dynamic Non-Line-of-Sight Imaging with Mamba Enforced Temporal Consistency
FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model
Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
Multi-objective Deep Data Generation with Correlated Property Control
The New Graph Kernels on Connectivity Networks for Identification of MCI
A Continuous Speech Recognition System Embedding MLP into HMM
Synthetic-to-Real Pose Estimation with Geometric Reconstruction
Debiasing Averaged Stochastic Gradient Descent to handle missing values
When Visual Prompt Tuning Meets Source-Free Domain Adaptive Semantic Segmentation
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition
CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses
MLP Can Provably Generalize Much Better than VC-bounds Indicate
What Makes Graph Neural Networks Miscalibrated?
Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization
Fast Exact Inference with a Factored Model for Natural Language Parsing
Training deep learning based denoisers without ground truth data
Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
Non-autoregressive Machine Translation with Probabilistic Context-free Grammar
Minimum Average Cost Clustering
Bayesian Inference of Regular Grammar and Markov Source Models
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback
VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Locally Adaptive Nearest Neighbor Algorithms
Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting
Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective
Spectral Methods for Learning Multivariate Latent Tree Structure
Quantifying the Cost of Learning in Queueing Systems
Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
Self-Supervised Multi-Object Tracking with Cross-input Consistency
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network
Self-Explaining Deviations for Coordination
Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts
L4: Practical loss-based stepsize adaptation for deep learning
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes
A General Method for Amortizing Variational Filtering
Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms
Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
Mixture weights optimisation for Alpha-Divergence Variational Inference
Balanced Chamfer Distance as a Comprehensive Metric for Point Cloud Completion
Offline Multitask Representation Learning for Reinforcement Learning
EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction
Identifying Fault-Prone Software Modules Using Feed-Forward Networks: A Case Study
Context-aware Synthesis and Placement of Object Instances
Convergence of $\text{log}(1/\epsilon)$ for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis
Data Sharing and Compression for Cooperative Networked Control
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values
Adversarial Moment-Matching Distillation of Large Language Models
Principled Bayesian Optimization in Collaboration with Human Experts
From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models
Improved Regret Bounds for Bandit Combinatorial Optimization
Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice
Spike timing-dependent plasticity as dynamic filter
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks
Episodic Memory in Lifelong Language Learning
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
Universally Quantized Neural Compression
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification
Extended Grassmann Kernels for Subspace-Based Learning
Learning to Augment Distributions for Out-of-distribution Detection
Learning by Choice of Internal Representations
Phase Transition from Clean Training to Adversarial Training
Multiscale Quantization for Fast Similarity Search
An Improved Analysis of Gradient Tracking for Decentralized Machine Learning
DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction
A benchmark of categorical encoders for binary classification
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers
FlowHMM: Flow-based continuous hidden Markov models
Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformers
Improving Certified Robustness via Statistical Learning with Logical Reasoning
Learning to Learn Variational Semantic Memory
Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
Time-Reversal Provides Unsupervised Feedback to LLMs
Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width
AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback
Parallel-mentoring for Offline Model-based Optimization
Learning to Play Sequential Games versus Unknown Opponents
Trust the Model When It Is Confident: Masked Model-based Actor-Critic
MMSite: A Multi-modal Framework for the Identification of Active Sites in Proteins
Boosting Decision Trees
Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model
Convergent Bounds on the Euclidean Distance
Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors
Flipping-based Policy for Chance-Constrained Markov Decision Processes
Learning SMaLL Predictors
Return of Unconditional Generation: A Self-supervised Representation Generation Method
A Contrast Sensitive Silicon Retina with Reciprocal Synapses
Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping
Neuro-Vision to Language: Enhancing Brain Recording-based Visual Reconstruction and Language Interaction
Private and Personalized Frequency Estimation in a Federated Setting
A Quadrature Rule combining Control Variates and Adaptive Importance Sampling
Learning Deep Features for Scene Recognition using Places Database
Ordering-based Conditions for Global Convergence of Policy Gradient Methods
SPoC: Search-based Pseudocode to Code
MultiOrg: A Multi-rater Organoid-detection Dataset
CLIPCEIL: Domain Generalization through CLIP via Channel rEfinement and Image-text aLignment
Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits
Inductive Regularized Learning of Kernel Functions
DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting
Imitation Learning from Vague Feedback
One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval
Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry
POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images
Discriminative Log-Linear Grammars with Latent Variables
Strategic Linear Contextual Bandits
ConvBERT: Improving BERT with Span-based Dynamic Convolution
Towards Optimal Effective Resistance Estimation
Sinkhorn Barycenter via Functional Gradient Descent
G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models
Value-Directed Compression of POMDPs
Continual Learning via Local Module Composition
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Evolving Learnable Languages
Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms
Hard Shape-Constrained Kernel Machines
Group and Topic Discovery from Relations and Their Attributes
Optimal learning rates for least squares SVMs using Gaussian kernels
WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking
Local-Global MCMC kernels: the best of both worlds
Two-Dimensional Linear Discriminant Analysis
Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
Provably Consistent Partial-Label Learning
Unsupervised Risk Estimation Using Only Conditional Independence Structure
Iterative Least Trimmed Squares for Mixed Linear Regression
Learned D-AMP: Principled Neural Network based Compressive Image Recovery
Into the Single Cell Multiverse: an End-to-End Dataset for Procedural Knowledge Extraction in Biomedical Texts
SUGARCREPE++ Dataset: Vision-Language Model Sensitivity to Semantic and Lexical Alterations
Self-supervised Co-Training for Video Representation Learning
A Theoretical Perspective for Speculative Decoding Algorithm
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory
DI-MaskDINO: A Joint Object Detection and Instance Segmentation Model
Pseudo-Likelihood Inference
YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus
Active Learning with Neural Networks: Insights from Nonparametric Statistics
How to transfer algorithmic reasoning knowledge to learn new algorithms?
Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning
Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos
UMB: Understanding Model Behavior for Open-World Object Detection
Perfect Dimensionality Recovery by Variational Bayesian PCA
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning
Open High-Resolution Satellite Imagery: The WorldStrat Dataset - With Application to Super-Resolution
Kernel Extraction via Voted Risk Minimization
VLMimic: Vision Language Models are Visual Imitation Learner for Fine-grained Actions