yusuke1997/dblp-id-title huggingface dataset:
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
The rat as particle filter
Discrimination-aware Channel Pruning for Deep Neural Networks
Scaling Law for Time Series Forecasting
Measures of Clustering Quality: A Working Set of Axioms for Clustering
Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck
Decoding of Neuronal Signals in Visual Pattern Recognition
Active Learning Applied to Patient-Adaptive Heartbeat Classification
Linear and Kernel Classification in the Streaming Model: Improved Bounds for Heavy Hitters
Hidden Markov Decision Trees
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics
Adaptive Clustering through Semidefinite Programming
Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning
Matrix Completion Under Monotonic Single Index Models
Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding
GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
Enhancing the Accuracy and Fairness of Human Decision Making
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning
CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions
State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory
DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization
DiffPhyCon: A Generative Approach to Control Complex Physical Systems
DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection
Hardness of Online Sleeping Combinatorial Optimization Problems
Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
Efficient Structured Matrix Rank Minimization
GENIE: Higher-Order Denoising Diffusion Solvers
Fast Image Deconvolution using Hyper-Laplacian Priors
Can fMRI reveal the representation of syntactic structure in the brain?
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm
Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion
Implicit Rank-Minimizing Autoencoder
Generalization Error Analysis of Quantized Compressive Learning
Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures
Multi-objective Maximization of Monotone Submodular Functions with Cardinality Constraint
Higher Order Recurrent Networks and Grammatical Inference
Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space
Meta-Learning Sparse Implicit Neural Representations
LIVE: Learnable In-Context Vector for Visual Question Answering
Lean Workbook: A large-scale Lean problem set formalized from natural language math problems
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks
The Price of Fair PCA: One Extra dimension
Evaluating the Moral Beliefs Encoded in LLMs
Plasticity-Mediated Competitive Learning
The least-control principle for local learning at equilibrium
Assistive Teaching of Motor Control Tasks to Humans
Incremental Few-Shot Learning with Attention Attractor Networks
Online control of the false discovery rate with decaying memory
The Doubly Correlated Nonparametric Topic Model
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving
Compositional Reinforcement Learning from Logical Specifications
Neural Graph Generation from Graph Statistics
Critical initialisation for deep signal propagation in noisy rectifier neural networks
Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping
Regression with Cost-based Rejection
PowerPM: Foundation Model for Power Systems
A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory
Exponential ergodicity of mirror-Langevin diffusions
DENSE: Data-Free One-Shot Federated Learning
(De)Randomized Smoothing for Certifiable Defense against Patch Attacks
Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces
An Improved Analysis of Stochastic Gradient Descent with Momentum
Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning
Improved learning rates in multi-unit uniform price auctions
Robust Contrastive Learning Using Negative Samples with Diminished Semantics
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs
A Deep-learning-aided Automatic Vision-based Control Approach for Autonomous Drone Racing in Game of Drones Competition
DreamCatcher: A Wearer-aware Multi-modal Sleep Event Dataset Based on Earables in Non-restrictive Environments
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach
Global Convergence and Stability of Stochastic Gradient Descent
An operator view of policy gradient methods
Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network
VLSI Phase Locking Architectures for Feature Linking in Multiple Target Tracking Systems
Model Compression with Adversarial Robustness: A Unified Optimization Framework
Hyper-HMM: aligning human brains and semantic features in a common latent event space
WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents
Predictive Querying for Autoregressive Neural Sequence Models
Metric from Human: Zero-shot Monocular Metric Depth Estimation via Test-time Adaptation
A Randomized Algorithm for Large Scale Support Vector Learning
Learning where to learn: Gradient sparsity in meta and continual learning
Robust Reinforcement Learning using Offline Data
Amortized Planning with Large-Scale Transformers: A Case Study on Chess
Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention
Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning
Linearly constrained Gaussian processes
Minimax Optimal Online Imitation Learning via Replay Estimation
On the Worst Prompt Performance of Large Language Models
Factorial Learning by Clustering Features
First-order Decomposition Trees
A Unifying Framework of Off-Policy General Value Function Evaluation
Sequential Context Encoding for Duplicate Removal
Trading off Consistency and Dimensionality of Convex Surrogates for Multiclass Classification
DDR: Exploiting Deep Degradation Response as Flexible Image Descriptor
On Robust Multiclass Learnability
Adversarial training for free!
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning
Locally-Adaptive Nonparametric Online Learning
Maximum Likelihood and the Information Bottleneck
Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels
MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models
On the connections between saliency and tracking
Hybrid Neural Autoencoders for Stimulus Encoding in Visual and Other Sensory Neuroprostheses
Factor Graph Neural Networks
DeWave: Discrete Encoding of EEG Waves for EEG to Text Translation
Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs
The Higgs boson machine learning challenge
Generalization Bounds via Conditional f-Information
Model-based Diffusion for Trajectory Optimization
Class-Incremental Learning via Dual Augmentation
Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation
StableFDG: Style and Attention Based Learning for Federated Domain Generalization
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Temporal Dynamic Quantization for Diffusion Models
ANODEV2: A Coupled Neural ODE Framework
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent
Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits
Structure-Aware Convolutional Neural Networks
C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses
A Tight Lower Bound and Efficient Reduction for Swap Regret
Networks with Learned Unit Response Functions
Poisson Flow Generative Models
Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs
FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space
Enhancing Q-Learning for Optimal Asset Allocation
Does a sparse ReLU network training problem always admit an optimum ?
Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
PaintSeg: Painting Pixels for Training-free Segmentation
Energy-based Out-of-distribution Detection
On Computing Probabilistic Explanations for Decision Trees
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles
Diversify & Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement
Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning
Posterior Matching for Arbitrary Conditioning
A Meta-Learning Perspective on Cold-Start Recommendations for Items
SpaRCS: Recovering low-rank and sparse matrices from compressive measurements
Silicon growth cones map silicon retina
Learning Infinite-Horizon Average-Reward Restless Multi-Action Bandits via Index Awareness
Distributed Inference in Dynamical Systems
Approximately Equivariant Neural Processes
Automatic Differentiation of Programs with Discrete Randomness
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters
The Mean-Squared Error of Double Q-Learning
Temporally Dependent Plasticity: An Information Theoretic Account
A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization
Equivariant Adaptation of Large Pretrained Models
Tensor Biclustering
Learning Beam Search Policies via Imitation Learning
Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories
MCVD - Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback
Sparsified SGD with Memory
Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss
Inferring Interaction Networks using the IBP applied to microRNA Target Prediction
Learning a Deep Compact Image Representation for Visual Tracking
Online Learning under Adversarial Nonlinear Constraints
Beyond Lazy Training for Over-parameterized Tensor Decomposition
FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow
Similarity Component Analysis
MVGamba: Unify 3D Content Generation as State Space Sequence Modeling
Learning Cut Generating Functions for Integer Programming
Blended Matching Pursuit
The Expressive Power of Neural Networks: A View from the Width
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
Continuous-Time Regression Models for Longitudinal Networks
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free
Dynamic Local Regret for Non-convex Online Forecasting
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
Differentially Private Contextual Linear Bandits
OceanBench: The Sea Surface Height Edition
Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
A Careful Examination of Large Language Model Performance on Grade School Arithmetic
C-Mixup: Improving Generalization in Regression
Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities
Projection Retrieval for Classification
Vision-Language Models are Strong Noisy Label Detectors
Hindsight Experience Replay
Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons
Advances in Neural Information Processing Systems 6, [7th NIPS Conference, Denver, Colorado, USA, 1993]
FreeAnchor: Learning to Match Anchors for Visual Object Detection
Emergence of Object-Selective Features in Unsupervised Feature Learning
On Learning Discrete Graphical Models using Greedy Methods
Grounding Neural Inference with Satisfiability Modulo Theories
Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs
Spectral Bias in Practice: The Role of Function Frequency in Generalization
Recovering Latent Causal Factor for Generalization to Distributional Shifts
Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently
Optimal spectral transportation with application to music transcription
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification
Focused Quantization for Sparse CNNs
ChatGPT-Powered Hierarchical Comparisons for Image Classification
Exploiting Domain-Specific Features to Enhance Domain Generalization
Synaptic Transmission: An Information-Theoretic Perspective
Vision GNN: An Image is Worth Graph of Nodes
On scalable oversight with weak LLMs judging strong LLMs
Efficient Learning of Discrete Graphical Models
Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models
Exploring Models and Data for Image Question Answering
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning
Backprop KF: Learning Discriminative Deterministic State Estimators
Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images
Robust Sparse Regression with Non-Isotropic Designs
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist
Equilibrated adaptive learning rates for non-convex optimization
On Binary Classification in Extreme Regions
Channel Permutations for N: M Sparsity
Biological Learning of Irreducible Representations of Commuting Transformations
On Reward-Free Reinforcement Learning with Linear Function Approximation
Discriminative Binaural Sound Localization
STEER : Simple Temporal Regularization For Neural ODE
Chaitin-Kolmogorov Complexity and Generalization in Neural Networks
Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999]
Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative MARL
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
Neural Lyapunov Control
Easy Regional Contrastive Learning of Expressive Fashion Representations
The Diversified Ensemble Neural Network
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization
Improving GANs with A Dynamic Discriminator
DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain
RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation
PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning
Slot-VLM: Object-Event Slots for Video-Language Modeling
Trajectory Convolution for Action Recognition
Connectionist Optimisation of Tied Mixture Hidden Markov Models
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs
Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo
Provably Efficient Offline Reinforcement Learning in Regular Decision Processes
Coresets for Classification - Simplified and Strengthened
Multimodal Deep Learning Model Unveils Behavioral Dynamics of V1 Activity in Freely Moving Mice
Transformers need glasses! Information over-squashing in language tasks
Distributed Principal Component Analysis with Limited Communication
Analog readout for optical reservoir computers
The Waymo Open Sim Agents Challenge
Group Sparse Coding
An Environment Model for Nonstationary Reinforcement Learning
Propagation Algorithms for Variational Bayesian Learning
Learning Unseen Modality Interaction
Opening the Vocabulary of Egocentric Actions
Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests
A Unified Switching System Perspective and Convergence Analysis of Q-Learning Algorithms
Integrate-and-Fire models with adaptation are good enough
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks
JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search
Critic Regularized Regression
Finding Consistencies in MEG Responses to Repeated Natural Speech
Improving PAC Exploration Using the Median Of Means
Video Instance Segmentation using Inter-Frame Communication Transformers
Emergence of Object Segmentation in Perturbed Generative Models
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
Content preserving text generation with attribute controls
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search
Learning State-Aware Visual Representations from Audible Interactions
Preconditioner Approximations for Probabilistic Graphical Models
NCDL: A Framework for Deep Learning on non-Cartesian Lattices
Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning
Model of a Biological Neuron as a Temporal Neural Network
Bayesian Model-Agnostic Meta-Learning
Seasons in Drift: A Long Term Thermal Imaging Dataset for Studying Concept Drift
The Unified Propagation and Scaling Algorithm
Stand-Alone Self-Attention in Vision Models
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning
A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents
Hippocampal Contributions to Control: The Third Way
Neural Image Compression: Generalization, Robustness, and Spectral Biases
Robust Implicit Networks via Non-Euclidean Contractions
Online Multitask Learning with Long-Term Memory
(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More
Bipartite Stochastic Block Models with Tiny Clusters
Graph Information Bottleneck
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient
Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters
Robust learning of low-dimensional dynamics from large neural ensembles
Fast subtree kernels on graphs
NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolation
BMRS: Bayesian Model Reduction for Structured Pruning
Practical 0.385-Approximation for Submodular Maximization Subject to a Cardinality Constraint
Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference
UniTSFace: Unified Threshold Integrated Sample-to-Sample Loss for Face Recognition
Extended and Unscented Gaussian Processes
Spectral Kernel Methods for Clustering
High-Dimensional Sparse Linear Bandits
Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations
Factorized Asymptotic Bayesian Inference for Latent Feature Models
Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory
Motion Graph Unleashed: A Novel Approach to Video Prediction
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding
Game Solving with Online Fine-Tuning
Generative Neural Fields by Mixtures of Neural Implicit Functions
Reciprocal Learning
Refined PID Controllers Using Neural Networks
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Explicable Reward Design for Reinforcement Learning Agents
Temporal Dynamics of Cognitive Control
On Certified Generalization in Structured Prediction
Subgame Solving in Adversarial Team Games
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
A Flexible Generative Framework for Graph-based Semi-supervised Learning
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
Learning Rich Rankings
Refining Language Models with Compositional Explanations
Convergence of adaptive algorithms for constrained weakly convex optimization
Efficient active learning of sparse halfspaces with arbitrary bounded noise
"Natural Images, Gaussian Mixtures and Dead Leaves"
(De-)Randomized Smoothing for Decision Stump Ensembles
From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion
Curriculum Disentangled Recommendation with Noisy Multi-feedback
Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform
Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond
Interaction-Grounded Learning with Action-Inclusive Feedback
Unsupervised Learning of Object Landmarks via Self-Training Correspondence
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited
Recovering Complete Actions for Cross-dataset Skeleton Action Recognition
To Trust Or Not To Trust A Classifier
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo
Centric Models of the Orientation Map in Primary Visual Cortex
Banded Square Root Matrix Factorization for Differentially Private Model Training
EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records
Learning under uncertainty: a comparison between R-W and Bayesian approach
SOI: Scaling Down Computational Complexity by Estimating Partial States of the Model
Adaptive Algorithms for Relaxed Pareto Set Identification
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences
GenS: Generalizable Neural Surface Reconstruction from Multi-View Images
H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion
Model Selection in Clustering by Uniform Convergence Bounds
Request Confirmation Networks for Neuro-Symbolic Script Execution
Positive Semidefinite Metric Learning with Boosting
Deep Set Prediction Networks
Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes
Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning
Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging
4Diffusion: Multi-view Video Diffusion Model for 4D Generation
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems
Towards Efficient and Accurate Winograd Convolution via Full Quantization
Relational Self-Attention: What's Missing in Attention for Video Understanding
Unraveling Molecular Structure: A Multimodal Spectroscopic Dataset for Chemistry
Operator Learning with Neural Fields: Tackling PDEs on General Geometries
On Differentially Private Graph Sparsification and Applications
Neural Lyapunov Control of Unknown Nonlinear Systems with Stability Guarantees
Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes
Deep Defense: Training DNNs with Improved Adversarial Robustness
FaceSync: A Linear Operator for Measuring Synchronization of Video Facial Images and Audio Tracks
CARE: Modeling Interacting Dynamics Under Temporal Environmental Variation
Towards robust vision by multi-task learning on monkey visual cortex
Brain covariance selection: better individual functional connectivity models using population prior