yusuke1997/dblp-id-title huggingface dataset:
Sampling weights of deep neural networks
Zero-Shot Event-Intensity Asymmetric Stereo via Visual Prompting from Image Domain
Regret based Robust Solutions for Uncertain Markov Decision Processes
Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
TGEA 2.0: A Large-Scale Diagnostically Annotated Dataset with Benchmark Tasks for Text Generation of Pretrained Language Models
Typicalness-Aware Learning for Failure Detection
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse
Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation
Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models
The Relevance Vector Machine
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations
Multi-Instance Multi-Label Learning with Application to Scene Classification
Submodular Maximization via Gradient Ascent: The Case of Deep Submodular Functions
Aligning to Thousands of Preferences via System Message Generalization
Hybrid Generative AI for De Novo Design of Co-Crystals with Enhanced Tabletability
Optimal and Fair Encouragement Policy Evaluation and Learning
On the Identifiability and Interpretability of Gaussian Process Models
Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective
Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Methods
Kernel Embeddings of Latent Tree Graphical Models
Randomized Experimental Design for Causal Graph Discovery
Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization
Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors
The Variational Ising Classifier (VIC) Algorithm for Coherently Contaminated Data
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data
Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima
SelecMix: Debiased Learning by Contradicting-pair Sampling
Adaptive Diffusion in Graph Neural Networks
Optimistic policy iteration and natural actor-critic: A unifying view and a non-optimality result
Reinforcement Learning with a Terminator
Contextually Affinitive Neighborhood Refinery for Deep Clustering
Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes
MaVEn: An Effective Multi-granularity Hybrid Visual Encoding Framework for Multimodal Large Language Model
Block Coordinate Plug-and-Play Methods for Blind Inverse Problems
Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising
VoxDet: Voxel Learning for Novel Instance Detection
Recursive Estimation of Dynamic Modular RBF Networks
Learning from Snapshots of Discrete and Continuous Data Streams
Iso-Dream: Isolating and Leveraging Noncontrollable Visual Dynamics in World Models
Simulation of Optimal Movements Using the Minimum-Muscle-Tension-Change Model
Collaborative Deep Learning in Fixed Topology Networks
Feature Selection Methods for Improving Protein Structure Prediction with Rosetta
Efficient Neural Music Generation
f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning
Using Unlabeled Data for Supervised Learning
A Convergent Form of Approximate Policy Iteration
How Neural Nets Work
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks
Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space
Distribution-Aware Data Expansion with Diffusion Models
How Diffusion Models Learn to Factorize and Compose
Efficient semidefinite-programming-based inference for binary and multi-class MRFs
Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis
Universal Rates for Interactive Learning
You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments
Testing Unfaithful Gaussian Graphical Models
A blind sparse deconvolution method for neural spike identification
Statistical and Dynamical Interpretation of ISIH Data from Periodically Stimulated Sensory Neurons
How the Catfish Tracks Its Prey: An Interactive 'Pipelined' Processing System May Direct Foraging via Reticulospinal Neurons
Global Convergence of Gradient Descent for Deep Linear Residual Networks
No-Regret Online Prediction with Strategic Experts
Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy
(Amplified) Banded Matrix Factorization: A unified approach to private training
Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence
Convergence and Energy Landscape for Cheeger Cut Clustering
Concentration of Data Encoding in Parameterized Quantum Circuits
Causal Categorization with Bayes Nets
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning
Statistical Learning for Resting-State fMRI: Successes and Challenges
Generalization Bounds in the Predict-then-Optimize Framework
Bit-Serial Neural Networks
Vision Transformers provably learn spatial structure
Probabilistic Principal Geodesic Analysis
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization
NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction
Consistency Models for Scalable and Fast Simulation-Based Inference
Bandits with Unobserved Confounders: A Causal Approach
Psychological Studies of Visual Perception
Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex
UniGAD: Unifying Multi-level Graph Anomaly Detection
Gibbs Sampling with People
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison
LinkNet: Relational Embedding for Scene Graph
Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient
Offline Reinforcement Learning with Differential Privacy
Dialog-based Language Learning
Temporal dynamics of information content carried by neurons in the primary visual cortex
Recursive Segmentation and Recognition Templates for 2D Parsing
Practical and Optimal LSH for Angular Distance
Reinforcement Learning for Call Admission Control and Routing in Integrated Service Networks
Towards Problem-dependent Optimal Learning Rates
The Multiscale Laplacian Graph Kernel
Nets with Unreliable Hidden Nodes Learn Error-Correcting Codes
Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness
ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training
The Multimodal Universe: Enabling Large-Scale Machine Learning with 100 TB of Astronomical Scientific Data
Reconciling "priors" & "priors" without prejudice?
Self-Adaptable Templates for Feature Coding
Experimental Design for Learning Causal Graphs with Latent Variables
Dis-inhibitory neuronal circuits can control the sign of synaptic plasticity
Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum
COHESIV: Contrastive Object and Hand Embedding Segmentation In Video
Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
Efficient Symmetric Norm Regression via Linear Sketching
DeepFoids: Adaptive Bio-Inspired Fish Simulation with Deep Reinforcement Learning
Really Doing Great at Estimating CATE? A Critical Look at ML Benchmarking Practices in Treatment Effect Estimation
Analysis of Sparse Bayesian Learning
Beyond Parity: Fairness Objectives for Collaborative Filtering
Bootstrap Model Aggregation for Distributed Statistical Learning
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
MaskPlace: Fast Chip Placement via Reinforced Visual Representation Learning
Distributed Power-law Graph Computing: Theoretical and Empirical Analysis
Pareto Domain Adaptation
User-Level Differential Privacy With Few Examples Per User
Biologically Plausible Local Learning Rules for the Adaptation of the Vestibulo-Ocular Reflex
IMED-RL: Regret optimal learning of ergodic Markov decision processes
Cluster Kernels for Semi-Supervised Learning
Elo Uncovered: Robustness and Best Practices in Language Model Evaluation
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation
A Central Limit Theorem for Differentially Private Query Answering
Explainability Via Causal Self-Talk
Q-DM: An Efficient Low-bit Quantized Diffusion Model
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Compressed Video Prompt Tuning
Unsupervised learning of object frames by dense equivariant image labelling
Graph Diffusion Transformers for Multi-Conditional Molecular Generation
Stochastic Multi-Armed Bandits with Control Variates
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach
Aligned Structured Sparsity Learning for Efficient Image Super-Resolution
Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought
LLaNA: Large Language and NeRF Assistant
Text Classification using String Kernels
Intrinsic dimensionality estimation using Normalizing Flows
AlterMOMA: Fusion Redundancy Pruning for Camera-LiDAR Fusion Models with Alternative Modality Masking
Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal
An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games
Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval
Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization
Agglomerative Multivariate Information Bottleneck
Bootstrapping Upper Confidence Bound
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees
Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach
User-Dependent Neural Sequence Models for Continuous-Time Event Data
A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model
Magnet: We Never Know How Text-to-Image Diffusion Models Work, Until We Learn How Vision-Language Models Function
The iNaturalist Sounds Dataset
A Non-parametric Direct Learning Approach to Heterogeneous Treatment Effect Estimation under Unmeasured Confounding
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing
Sequentially Fitting "Inclusive" Trees for Inference in Noisy-OR Networks
Coarse-to-Fine Concept Bottleneck Models
Particle Semi-Implicit Variational Inference
Robust large-margin learning in hyperbolic space
Privacy Amplification via Random Check-Ins
Visual Anchors Are Strong Information Aggregators For Multimodal Large Language Model
Training Neural Networks is NP-Hard in Fixed Dimension
Generalized Linear Bandits with Local Differential Privacy
RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models
Towards Practical Alternating Least-Squares for CCA
Conditional Generative Moment-Matching Networks
Advances in Neural Information Processing Systems 9, NIPS, Denver, CO, USA, December 2-5, 1996
Semi-supervised MarginBoost
Relating Hopfield Networks to Episodic Control
Figure of Merit Training for Detection and Spotting
Minimum Description Length and Generalization Guarantees for Representation Learning
Biases for Emergent Communication in Multi-agent Reinforcement Learning
Semi-supervised Multi-label Learning with Balanced Binary Angular Margin Loss
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
Knowledge Graph Completion by Intermediate Variables Regularization
An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval
Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation
Learning with Feature Evolvable Streams
ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions
Tree-based reparameterization for approximate inference on loopy graphs
Graph-based Uncertainty Metrics for Long-form Language Model Generations
Joint Probabilistic Curve Clustering and Alignment
Few-Shot Learning Evaluation in Natural Language Understanding
Texture Interpolation for Probing Visual Perception
Policy Gradient Coagent Networks
SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image Classification
USB: A Unified Semi-supervised Learning Benchmark for Classification
Loki: Low-rank Keys for Efficient Sparse Attention
Sequential effects reflect parallel learning of multiple environmental regularities
Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models
Do Residual Neural Networks discretize Neural Ordinary Differential Equations?
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?
A posteriori error bounds for joint matrix decomposition problems
A Hidden Markov Model for de Novo Peptide Sequencing
The Fast Convergence of Incremental PCA
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem
Learning World Models with Identifiable Factorization
LLaMo: Large Language Model-based Molecular Graph Assistant
Nonlinear Learning using Local Coordinate Coding
Learning Curves for Gaussian Processes
Video Prediction via Selective Sampling
UniDoc: Unified Pretraining Framework for Document Understanding
ContextGS : Compact 3D Gaussian Splatting with Anchor Level Context Model
Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits
Learning the Infinitesimal Generator of Stochastic Diffusion Processes
GeoNLF: Geometry guided Pose-Free Neural LiDAR Fields
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
Gradient-Based Feature Learning under Structured Data
Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization
DAPE: Data-Adaptive Positional Encoding for Length Extrapolation
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone
CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object Detection
Monaural Speech Separation
Geometry-Aware Neural Rendering
VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
Developing Population Codes by Minimizing Description Length
When Counterpoint Meets Chinese Folk Melodies
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning
Conformal Prediction Sets for Ordinal Classification
Bayesian PCA
Extensive-Form Game Solving via Blackwell Approachability on Treeplexes
Fast Distributed Submodular Cover: Public-Private Data Summarization
Inverse Preference Learning: Preference-based RL without a Reward Function
A Communication-Efficient Parallel Algorithm for Decision Tree
Controlled Recognition Bounds for Visual Learning and Exploration
Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes
Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings
Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization
Provable Overlapping Community Detection in Weighted Graphs
Mirror Descent Meets Fixed Share (and feels no regret)
TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification
Bayesian estimation of discrete entropy with mixtures of stick-breaking priors
Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization
Neural Information Processing Systems, Denver, Colorado, USA, 1987
Adversarial Example Games
Policy Gradient Methods for Reinforcement Learning with Function Approximation
DataComp-LM: In search of the next generation of training sets for language models
Efficient Diffusion Policies For Offline Reinforcement Learning
A Non-generative Framework and Convex Relaxations for Unsupervised Learning
Direct Multi-Step Time Series Prediction Using TD-lambda
Computing regularization paths for learning multiple kernels
Learning to Segment Images Using Dynamic Feature Binding
Foundation Model is Efficient Multimodal Multitask Model Selector
Learning latent variable structured prediction models with Gaussian perturbations
Matrix Norm Estimation from a Few Entries
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
Exploration by Learning Diverse Skills through Successor State Representations
Neural Networks that Learn to Discriminate Similar Kanji Characters
Empirical Risk Minimization Under Fairness Constraints
Multiple Paired Forward-Inverse Models for Human Motor Learning and Control
DG-SLAM: Robust Dynamic Gaussian Splatting SLAM with Hybrid Pose Optimization
Relative Loss Bounds for Multidimensional Regression Problems
Coarse-to-Fine Image Search Using Neural Networks
Generic bounds on the approximation error for physics-informed (and) operator learning
Weight Agnostic Neural Networks
Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach
Lazy Learning Meets the Recursive Least Squares Algorithm
A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation
SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures
Grounded Video Situation Recognition
Collective Graphical Models
A Variational Perspective on High-Resolution ODEs
Learning Macro-Actions in Reinforcement Learning
On the Complexity of Adversarial Decision Making
Learning Distinguishable Trajectory Representation with Contrastive Loss
Causal inference in sensorimotor integration
ProxyFusion: Face Feature Aggregation Through Sparse Experts
Learning optimal spike-based representations
Interferobot: aligning an optical interferometer by a reinforcement learning agent
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation
Unsupervised Object-Based Transition Models For 3D Partially Observable Environments
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
Probabilistic Neural Programmed Networks for Scene Generation
A Theory of Optimistically Universal Online Learnability for General Concept Classes
Robust Matrix Sensing in the Semi-Random Model
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
Generalization and Parameter Estimation in Feedforward Netws: Some Experiments
Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time
Understanding Deep Architecture with Reasoning Layer
The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning
Periodic Step Size Adaptation for Single Pass On-line Learning
Learning a Hierarchical Belief Network of Independent Factor Analyzers
Sparse Estimation Using General Likelihoods and Non-Factorial Priors
Semi-supervised Learning on Directed Graphs
Taxonomizing local versus global structure in neural network loss landscapes
Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling
Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality
Self-supervised Amodal Video Object Segmentation
SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain
On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution
Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology
Language Models can Solve Computer Tasks
Affine-Invariant Online Optimization and the Low-rank Experts Problem
Zero-shot Visual Relation Detection via Composite Visual Cues from Large Language Models
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds
SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction
Continual Learning for Instruction Following from Realtime Feedback
Variational Gaussian-process factor analysis for modeling spatio-temporal data
DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data
Finding Transformer Circuits With Edge Pruning
Tight Complexity Bounds for Optimizing Composite Objectives
Online Learning with Switching Costs and Other Adaptive Adversaries
Particle Filter-based Policy Gradient in POMDPs
Improved Utility Analysis of Private CountSketch
Distributional Convergence of the Sliced Wasserstein Process
Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses
Chromatic Correlation Clustering, Revisited
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
Global Sensitivity Analysis for MAP Inference in Graphical Models
Large-scale optimal transport map estimation using projection pursuit
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks
Multiclass Learning by Probabilistic Embeddings
Action-Model Based Multi-agent Plan Recognition
Online Bayesian Persuasion
Linear Multilayer Independent Component Analysis for Large Natural Scenes
Learning Nonparametric Models for Probabilistic Imitation
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure
On Margin Maximization in Linear and ReLU Networks
DDGS-CT: Direction-Disentangled Gaussian Splatting for Realistic Volume Rendering
Causal Estimation with Functional Confounders
Mixture of neural fields for heterogeneous reconstruction in cryo-EM
Differentially Private Bayesian Linear Regression
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization
Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data
Learning interacting dynamical systems with latent Gaussian process ODEs
Free energy score space
Reward learning from human preferences and demonstrations in Atari
Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA
Is Value Learning Really the Main Bottleneck in Offline RL?
Scalable Thompson Sampling using Sparse Gaussian Process Models
Derivative-enhanced Deep Operator Network
Contrastive Reinforcement Learning of Symbolic Reasoning Domains
Microstructures and Accuracy of Graph Recall by Large Language Models
Expanding Sparse Tuning for Low Memory Usage
Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation
Bandits Dueling on Partially Ordered Sets
RealMAN: A Real-Recorded and Annotated Microphone Array Dataset for Dynamic Speech Enhancement and Localization
Diverse Conventions for Human-AI Collaboration
Adaptive Data Augmentation on Temporal Graphs
Decision Jungles: Compact and Rich Models for Classification
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
Planning for Sample Efficient Imitation Learning
Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions
On the Fairness of Disentangled Representations