yusuke1997/dblp-id-title huggingface dataset:
An adaptive Mirror-Prox method for variational inequalities with singular operators
Group Equivariant Capsule Networks
Contrastive Learning as Goal-Conditioned Reinforcement Learning
Non-Cooperative Inverse Reinforcement Learning
Learning A Structured Optimal Bipartite Graph for Co-Clustering
An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective
EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries
Foundation Inference Models for Markov Jump Processes
Multi-Task Bayesian Optimization
Intrinsically Motivated Reinforcement Learning
On the Efficiency of ERM in Feature Learning
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model
Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints
Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models
Optimizing Correlation Algorithms for Hardware-Based Transient Classification
Sliced Gromov-Wasserstein
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations
OccFusion: Rendering Occluded Humans with Generative Diffusion Priors
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
Asymmetric Valleys: Beyond Sharp and Flat Local Minima
A PAC-Bayes Analysis of Adversarial Robustness
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-and-Language Pre-training
Mind the Nuisance: Gaussian Process Classification using Privileged Noise
Predicting response time and error rates in visual search
Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings
Learning Spike-Based Correlations and Conditional Probabilities in Silicon
Deterministic Single-Pass Algorithm for LDA
SceneCraft: Layout-Guided 3D Scene Generation
GeoPlant: Spatial Plant Species Prediction Dataset
Robust Quantization: One Model to Rule Them All
Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli
A Silicon Model of Amplitude Modulation Detection in the Auditory Brainstem
Reconciling λ-Returns with Experience Replay
Online Prediction at the Limit of Zero Temperature
Meta-learning with an Adaptive Task Scheduler
Conditional Models on the Ranking Poset
Mapping paradigm ontologies to and from the brain
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
AED: Adaptable Error Detection for Few-shot Imitation Policy
Masked Autoencoders As Spatiotemporal Learners
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
HOGWILD!-Gibbs can be PanAccurate
Beyond the Birkhoff Polytope: Convex Relaxations for Vector Permutation Problems
Light Unbalanced Optimal Transport
ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's
Learning Structural Equation Models for fMRI
Scalable and Efficient Non-adaptive Deterministic Group Testing
Support Vector Regression Machines
AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning
Lower Boundaries of Motoneuron Desynchronization via Renshaw Interneurons
Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning
CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM
Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
Theoretical Foundations of Deep Selective State-Space Models
Multi-objective Bayesian optimisation with preferences over objectives
What can linearized neural networks actually say about generalization?
Stochastic Hillclimbing as a Baseline Mathod for Evaluating Genetic Algorithms
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds
Plant-and-Steal: Truthful Fair Allocations via Predictions
Empirical models of spiking in neural populations
Parameterizing Non-Parametric Meta-Reinforcement Learning Tasks via Subtask Decomposition
The motion planning neural circuit in goal-directed navigation as Lie group operator search
Spectral Relaxation for K-means Clustering
Rectangular Bounding Process
Smooth And Consistent Probabilistic Regression Trees
Fast Parallel Algorithms for Statistical Subset Selection Problems
CSPG: Crossing Sparse Proximity Graphs for Approximate Nearest Neighbor Search
Differentiable sorting for censored time-to-event data
CommonsenseQA 2.0: Exposing the Limits of AI through Gamification
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores
NIPS Workshop on Imperfect Decision Makers 2016: Preface
Learning to Receive Help: Intervention-Aware Concept Embedding Models
(Almost) No Label No Cry
Wormholes Improve Contrastive Divergence
Online Submodular Set Cover, Ranking, and Repeated Active Learning
A Linear-Time Kernel Goodness-of-Fit Test
Bias and variance of the Bayesian-mean decoder
Higgs Boson Discovery with Boosted Trees
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression
Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures
Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent
Private Online Learning via Lazy Algorithms
Model Based Population Tracking and Automatic Detection of Distribution Changes
Optimality of variational inference for stochasticblock model with missing links
Deep Fourier Up-Sampling
Prediction on a Graph with a Perceptron
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
Following Curved Regularized Optimization Solution Paths
Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system
How many classifiers do we need?
Neural Network Recognizer for Hand-Written Zip Code Digits
Optimal Stochastic Search and Adaptive Momentum
Learning to Schedule Heuristics in Branch and Bound
Dynamic pricing and assortment under a contextual MNL demand
Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations
NVRC: Neural Video Representation Compression
A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
Monte Carlo POMDPs
A Minimax Optimal Algorithm for Crowdsourcing
The Multi-fidelity Multi-armed Bandit
Unsupervised learning models of primary cortical receptive fields and receptive field plasticity
Open-Vocabulary Object Detection via Language Hierarchy
Active Instance Sampling via Matrix Partition
Parallelizing Linear Transformers with the Delta Rule over Sequence Length
Active Learning for Multiple Target Models
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
Convolutional Phase Retrieval
Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms
Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions
CageNeRF: Cage-based Neural Radiance Field for Generalized 3D Deformation and Animation
Equivariant Networks for Crystal Structures
Confident Natural Policy Gradient for Local Planning in q π -realizable Constrained MDPs
Conservative Dual Policy Optimization for Efficient Model-Based Reinforcement Learning
ConceptFactory: Facilitate 3D Object Knowledge Annotation with Object Conceptualization
Bandit Task Assignment with Unknown Processing Time
Deep Reinforcement and InfoMax Learning
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks
Early Brain Damage
Examples of learning curves from a modified VC-formalism
Few-Shot Adversarial Prompt Learning on Vision-Language Models
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks
Generative Smoke Removal
Resource-Aware Federated Self-Supervised Learning with Global Class Representations
Active dendrites: adaptation to spike-based communication
Model Similarity Mitigates Test Set Overuse
A latent factor model for highly multi-relational data
Mallows Models for Top-k Lists
On Kernel-Target Alignment
ReAct: Out-of-distribution Detection With Rectified Activations
Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation
Bias-Optimal Incremental Problem Solving
Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering
Probabilistic size-and-shape functional mixed models
Sequential effects: Superstition or rational behavior?
Fundamental Limits of Budget-Fidelity Trade-off in Label Crowdsourcing
Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models
On permutation symmetries in Bayesian neural network posteriors: a variational perspective
Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation
Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions
Multi-objects Generation with Amortized Structural Regularization
Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation
Graph Stochastic Neural Networks for Semi-supervised Learning
Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge
ENAT: Rethinking Spatial-temporal Interactions in Token-based Image Synthesis
Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily
Non-stationary Bandits with Knapsacks
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
Designed Measurements for Vector Count Data
Approximating MAP by Compensating for Structural Relaxations
Generalizable and Animatable Gaussian Head Avatar
A Unified Framework for Extensive-Form Game Abstraction with Bounds
An inner-loop free solution to inverse problems using deep neural networks
Affinity-Aware Graph Networks
The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference
A Mean-Field Game Approach to Cloud Resource Management with Function Approximation
Zipfian Whitening
On the Importance of Gradient Norm in PAC-Bayesian Bounds
Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction
EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records
Provably Robust Metric Learning
PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points
Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies
ClimbQ: Class Imbalanced Quantization Enabling Robustness on Efficient Inferences
RAMP: Boosting Adversarial Robustness Against Multiple l p Perturbations for Universal Robustness
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models
What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration
Boundary Decomposition for Nadir Objective Vector Estimation
Representing Hyperbolic Space Accurately using Multi-Component Floats
Decoding-Time Language Model Alignment with Multiple Objectives
Learning Bregman Divergences with Application to Robustness
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
Learning Time-Varying Coverage Functions
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition
A Faster Decentralized Algorithm for Nonconvex Minimax Problems
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Unlocking the Capabilities of Masked Generative Models for Image Synthesis via Self-Guidance
Generalized roof duality and bisubmodular functions
Infinite Factorial Dynamical Model
Sample-Efficient Reinforcement Learning of Undercomplete POMDPs
Clustering with a Domain-Specific Distance Measure
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning
Learning and Tracking Cyclic Human Motion
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
Mixed-Initiative Multiagent Apprenticeship Learning for Human Training of Robot Teams
Occlusion Detection and Motion Estimation with Convex Optimization
Lookaround Optimizer: k steps around, 1 step average
Inferring Generative Model Structure with Static Analysis
Deep Conditional Gaussian Mixture Model for Constrained Clustering
Continuous MDP Homomorphisms and Homomorphic Policy Gradient
Learning to Select Best Forecast Tasks for Clinical Outcome Prediction
Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions
Maximum Independent Set: Self-Training through Dynamic Programming
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
Linear Dependent Dimensionality Reduction
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark
Adversarial Teacher-Student Representation Learning for Domain Generalization
Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads
Strategy Grafting in Extensive Games
Recovering Perspective Pose with a Dual Step EM Algorithm
Goal-Conditioned On-Policy Reinforcement Learning
Adapting to Online Label Shift with Provable Guarantees
Geometric Transformer with Interatomic Positional Encoding
ProPILE: Probing Privacy Leakage in Large Language Models
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models
BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset
Online Variational Filtering and Parameter Learning
Coupled Segmentation and Edge Learning via Dynamic Graph Propagation
Compact task representations as a normative model for higher-order brain activity
Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training
A Computer Modeling Approach to Understanding the Inferior Olive and Its Relationships to the Cerebellar Cortex in Rats
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization
TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning
Algorithms and Theory for Multiple-Source Adaptation
Stable and expressive recurrent vision models
Challenging Common Assumptions in Convex Reinforcement Learning
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
MetaAnchor: Learning to Detect Objects with Customized Anchors
Rethinking Graph Transformers with Spectral Attention
FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information
Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources
Learning to run a Power Network Challenge: a Retrospective Analysis
Causal Component Analysis
When is Agnostic Reinforcement Learning Statistically Tractable?
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning
Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?
Communication Compression for Decentralized Training
Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-Exploration
Out-of-Distribution Detection with a Single Unconditional Diffusion Model
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification
Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations
On the Exploitability of Instruction Tuning
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
Context-Based Dynamic Pricing with Partially Linear Demand Model
Simple and Asymmetric Graph Contrastive Learning without Augmentations
A New Multi-Source Light Detection Benchmark and Semi-Supervised Focal Light Detection
Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
GS-Hider: Hiding Messages into 3D Gaussian Splatting
Symbolic Regression with a Learned Concept Library
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning
Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems
On the Inductive Bias of Stacking Towards Improving Reasoning
A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
Minimum Bayes Error Feature Selection for Continuous Speech Recognition
EpiGRAF: Rethinking training of 3D GANs
Exact natural gradient in deep linear networks and its application to the nonlinear case
A fast, universal algorithm to learn parametric nonlinear embeddings
DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
When do random forests fail?
A Neural Network Approach for Three-Dimensional Object Recognition
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
Regularized Behavior Cloning for Blocking the Leakage of Past Action Information
Delving into the Reversal Curse: How Far Can Large Language Models Generalize?
An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer
Self-Supervised Learning with Kernel Dependence Maximization
Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models
Bayesian Backpropagation Over I-O Functions Rather Than Weights
A Short-Term Memory Architecture for the Learning of Morphophonemic Rules
Neural Reconstruction with Approximate Message Passing (NeuRAMP)
An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap
Contrastive Learning of Global and Local Video Representations
Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog
Learning Mixtures of Gaussians Using the DDPM Objective
Proximal Learning With Opponent-Learning Awareness
Certifying Geometric Robustness of Neural Networks
Adaptive Passive-Aggressive Framework for Online Regression with Side Information
Credal Self-Supervised Learning
Domain Generalization via Model-Agnostic Learning of Semantic Features
Open-Book Neural Algorithmic Reasoning
Intra-Processing Methods for Debiasing Neural Networks
Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity
Multi-Class $H$-Consistency Bounds
Riffled Independence for Ranked Data
Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits
Revisiting Smoothed Online Learning
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint
Deep Submodular Peripteral Networks
Fight Back Against Jailbreaking via Prompt Adversarial Tuning
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
Look-ahead Meta Learning for Continual Learning
Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick
A rational model of preference learning and choice prediction by children
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit
Learning with User-Level Privacy
Order Optimal One-Shot Distributed Learning
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote
Semiparametric Differential Graph Models
Causal Strategic Inference in Networked Microfinance Economies
Similarity-based cooperative equilibrium
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
Generalized Inverse Optimization through Online Learning
Skinned Motion Retargeting with Dense Geometric Interaction Perception
Fast Training of Pose Detectors in the Fourier Domain
CLIPAway: Harmonizing focused embeddings for removing objects via diffusion models
MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making
Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction
A Normative and Biologically Plausible Algorithm for Independent Component Analysis
First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context
Protein Design with Guided Discrete Diffusion
Discovering the Structure of a Reactive Environment by Exploration
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
Deep Sets
On the Complexity of Learning the Kernel Matrix
A variational approximate posterior for the deep Wishart process
A Reinforcement Learning Theory for Homeostatic Regulation
Beyond Pairwise: Provably Fast Algorithms for Approximate k -Way Similarity Search
Convex Neural Networks
Uncovering Meanings of Embeddings via Partial Orthogonality
MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities
On the Trade-off between Adversarial and Backdoor Robustness
Nonlinear dynamics of localization in neural receptive fields
SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation
An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions
Variational Mixture of Gaussian Process Experts
Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection
On the Separation of Signals from Neighboring Cells in Tetrode Recordings
Combinatorial semi-bandit with known covariance
Localized Structured Prediction
Bounded Regret for Finite-Armed Structured Bandits
Modulating early visual processing by language
Online Learning with Costly Features and Labels
Sparse Graphical Memory for Robust Planning
Towards Comprehensive Detection of Chinese Harmful Memes
Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces
Fast Determinantal Point Process Sampling with Application to Clustering
Physics-Constrained Comprehensive Optical Neural Networks
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks
Dynamical And-Or Graph Learning for Object Shape Modeling and Detection
Inexact trust-region algorithms on Riemannian manifolds
On the Generalization Properties of Diffusion Models
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness
Self-Evaluation Guided Beam Search for Reasoning
Neural Oscillators are Universal
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution
Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective
Estimating Convergence of Markov chains with L-Lag Couplings
Memory-efficient Patch-based Inference for Tiny Deep Learning
Operator Variational Inference
PaCE: Parsimonious Concept Engineering for Large Language Models
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs
Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM
Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems