yusuke1997/dblp-id-title huggingface dataset:
Diffusion Self-Guidance for Controllable Image Generation
Improved Particle Approximation Error for Mean Field Neural Networks
Supervised Learning for Dynamical System Learning
Communication-Optimal Distributed Clustering
Unsupervised Learning of Spoken Language with Visual Context
Scaling laws for learning with real and surrogate data
Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents
Online Learning with Adversarial Delays
Improving Intrinsic Exploration with Language Abstractions
Where does In-context Learning Happen in Large Language Models?
Small batch deep reinforcement learning
A Practice Strategy for Robot Learning Control
Provably Correct Automatic Sub-Differentiation for Qualified Programs
Generating QM1B with PySCF IPU
Projected Natural Actor-Critic
Neural Network Implementation Approaches for the Connection Machine
An Analog VLSI Saccadic Eye Movement System
Optimal Binary Classification Beyond Accuracy
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
Unmixing Hyperspectral Data
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency
On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting
Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model
Faster Ridge Regression via the Subsampled Randomized Hadamard Transform
InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations
Discriminator optimal transport
UCB-based Algorithms for Multinomial Logistic Regression Bandits
Data Market Design through Deep Learning
Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets
Supervised Sparse Analysis and Synthesis Operators
Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models
Bandit Learning with Delayed Impact of Actions
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit
Structured ranking learning using cumulative distribution networks
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability
RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer
Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards
An Exact Characterization of the Generalization Error for the Gibbs Algorithm
Mass-Producing Failures of Multimodal Systems with Language Models
An Empirical Study on Disentanglement of Negative-free Contrastive Learning
Online Prediction of Switching Graph Labelings with Cluster Specialists
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics
Exploring Length Generalization in Large Language Models
Unsupervised Structure Learning of Stochastic And-Or Grammars
Amortized Inference Regularization
Once Read is Enough: Domain-specific Pretraining-free Language Models with Cluster-guided Sparse Experts for Long-tail Domain Knowledge
Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates
Familiarity Discrimination of Radar Pulses
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
Regression under demographic parity constraints via unlabeled post-processing
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE
SeafloorAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey
Intelligent Sight and Sound: A Chronic Cancer Facial Pain Dataset
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
A simple neural network module for relational reasoning
Learning Graph Representations with Embedding Propagation
Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices
Data Visualization and Feature Selection: New Algorithms for Nongaussian Data
Segmentation as Maximum-Weight Independent Set
Forecasting Demand for Electric Power
RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Probabilistic latent variable models for distinguishing between cause and effect
Asymptotically Best Causal Effect Identification with Multi-Armed Bandits
Dual Critic Reinforcement Learning under Partial Observability
Deep Stochastic Processes via Functional Markov Transition Operators
Forward Dynamics Modeling of Speech Motor Control Using Physiological Data
Deep linear networks for regression are implicitly regularized towards flat minima
Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds
Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation
A Safe Screening Rule for Sparse Logistic Regression
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time
Faster Wasserstein Distance Estimation with the Sinkhorn Divergence
Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking Neurons
X-CAL: Explicit Calibration for Survival Analysis
A Gradient Accumulation Method for Dense Retriever under Memory Constraint
Procedural Image Programs for Representation Learning
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
Action-Conditional Video Prediction using Deep Networks in Atari Games
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
Human Decision-Making under Limited Time
Model Selection for Production System via Automated Online Experiments
Runtime Neural Pruning
Neural Expectation Maximization
Reconstruction for Powerful Graph Representations
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Gaussian Mixture Solvers for Diffusion Models
Benchmark Data Repositories for Better Benchmarking
Bounding and Approximating Intersectional Fairness through Marginal Fairness
Listening to Sounds of Silence for Speech Denoising
Face2QR: A Unified Framework for Aesthetic, Face-Preserving, and Scannable QR Code Generation
On Robustness to Adversarial Examples and Polynomial Optimization
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning
Implicit Semantic Data Augmentation for Deep Networks
Sinkhorn Distances: Lightspeed Computation of Optimal Transport
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
Basis-Function Trees as a Generalization of Local Variable Selection Methods
Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex
ADGym: Design Choices for Deep Anomaly Detection
A Hybrid Neural Net System for State-of-the-Art Continuous Speech Recognition
Mode Estimation for High Dimensional Discrete Tree Graphical Models
Feedback control guides credit assignment in recurrent neural networks
Feature Correspondence: A Markov Chain Monte Carlo Approach
Supervised Training of Conditional Monge Maps
Measuring Neural Net Robustness with Constraints
BERTs are Generative In-Context Learners
Better SGD using Second-order Momentum
Truth is Universal: Robust Detection of Lies in LLMs
Human-Adversarial Visual Question Answering
Turbo Learning for CaptionBot and DrawingBot
Structured sparsity-inducing norms through submodular functions
Learning from Label Proportions: A Mutual Contamination Framework
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Learning with Noisy Correspondence for Cross-modal Matching
Exploiting Correlated Auxiliary Feedback in Parameterized Bandits
Accelerating Relative Entropy Coding with Space Partitioning
DEX: Data Channel Extension for Efficient CNN Inference on Tiny AI Accelerators
Discriminating Deformable Shape Classes
Joint Policy Search for Multi-agent Collaboration with Imperfect Information
SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping
Hybrid Knowledge Routed Modules for Large-scale Object Detection
Strategizing against No-regret Learners
OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding
Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk
Implicit Posterior Variational Inference for Deep Gaussian Processes
Using Statistics to Automate Stochastic Optimization
Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion
BubbleML: A Multiphase Multiphysics Dataset and Benchmarks for Machine Learning
Zero-Shot Video Question Answering via Frozen Bidirectional Language Models
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion
Collaborative Causal Discovery with Atomic Interventions
VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought
Affinity Clustering: Hierarchical Clustering at Scale
Removing Hidden Confounding by Experimental Grounding
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner
Foundations of Comparison-Based Hierarchical Clustering
Test-Time Dynamic Image Fusion
Learning to Correlate in Multi-Player General-Sum Sequential Games
Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge
Learning Nonparametric Volterra Kernels with Gaussian Processes
Variational Linear Response
Transfer Learning with Affine Model Transformation
Make One-Shot Video Object Segmentation Efficient Again
Analog VLSI Cellular Implementation of the Boundary Contour System
Fast and Accurate $k$-means++ via Rejection Sampling
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks
Hybrid Search for Efficient Planning with Completeness Guarantees
On the Stability and Generalization of Meta-Learning
A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration
Vidu4D: Single Generated Video to High-Fidelity 4D Reconstruction with Dynamic Gaussian Surfels
WT-MVSNet: Window-based Transformers for Multi-view Stereo
LeDex: Training LLMs to Better Self-Debug and Explain Code
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models
Multiple Incremental Decremental Learning of Support Vector Machines
Character-level Convolutional Networks for Text Classification
Improving Black-box Adversarial Attacks with a Transfer-based Prior
Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose Reconstruction
JAWS: Auditing Predictive Uncertainty Under Covariate Shift
Generator Identification for Linear SDEs with Additive and Multiplicative Noise
Enhancing Safe Exploration Using Safety State Augmentation
BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays
Collegial Ensembles
Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes
LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
Visual Data Diagnosis and Debiasing with Concept Graphs
Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
Invariant Representations without Adversarial Training
Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization
Sparse Greedy Gaussian Process Regression
Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees
Green's Function Method for Fast On-Line Learning Algorithm of Recurrent Neural Networks
First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time
MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation
Cyclic Equilibria in Markov Games
Communication-Efficient Distributed Dual Coordinate Ascent
Nuclear Norm Regularization for Deep Learning
Optimizing Reusable Knowledge for Continual Learning via Metalearning
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning
Illumination-Invariant Face Recognition with a Contrast Sensitive Silicon Retina
Maaping Between Neural and Physical Activities of the Lobster Gastric Mill
A Canonicalization Perspective on Invariant and Equivariant Learning
Fairness without Demographics through Knowledge Distillation
MatrixNet: Learning over symmetry groups using learned group representations
The Infinite Mixture of Infinite Gaussian Mixtures
Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models
Learning Causal Structures Using Regression Invariance
Retrieved context and the discovery of semantic structure
Deep Reinforcement Learning from Human Preferences
Online Weighted Paging with Unknown Weights
Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework
From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach
An Integer Optimization Approach to Associative Classification
Sampling Sketches for Concave Sublinear Functions of Frequencies
On the Ability of Developers' Training Data Preservation of Learnware
Explicit Disentanglement of Appearance and Perspective in Generative Models
Generative Image Translation for Data Augmentation in Colorectal Histopathology Images
Revenue maximization via machine learning with noisy data
Applications of Neural Networks in Video Signal Processing
A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions
Solving Non-smooth Constrained Programs with Lower Complexity than \mathcal{O}(1/\varepsilon): A Primal-Dual Homotopy Smoothing Approach
On the Convergence Rate of Training Recurrent Neural Networks
MT2: Multi-task Mean Teacher for Semi-Supervised Cell Segmentation
Online Models for Content Optimization
Causal Inference on Time Series using Restricted Structural Equation Models
Efficient Anomaly Detection via Matrix Sketching
Sampling with Trusthworthy Constraints: A Variational Gradient Framework
Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication
LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training
Exact Verification of ReLU Neural Control Barrier Functions
Large-scale biophysical parameter estimation in single neurons via constrained linear regression
Transfer of Value Functions via Variational Methods
Maximum Margin Multi-Label Structured Prediction
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Towards Lightweight Black-Box Attack Against Deep Neural Networks
Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces
Learning Non-Linear Combinations of Kernels
Neural Network On-Line Learning Control of Spacecraft Smart Structures
Exclusive Feature Learning on Arbitrary Structures via \ell_{1, 2}-norm
SALSA: Attacking Lattice Cryptography with Transformers
A Connectionist Learning Approach to Analyzing Linguistic Stress
Monte Carlo Tree Search with Boltzmann Exploration
Consistent Kernel Mean Estimation for Functions of Random Variables
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
Online Robust Reinforcement Learning with Model Uncertainty
Retrospective on the SENSORIUM 2022 competition
Generalized Eigenvalue Problems with Generative Priors
Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity
Neural Universal Discrete Denoiser
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks
Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI
Statistical Mechanics of the Mixture of Experts
Review Networks for Caption Generation
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
Recurrent Kernel Networks
Learnability and the doubling dimension
Dynamical Causal Learning
Learning to dehaze with polarization
Adversarial Task Up-sampling for Meta-learning
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-World Document Analysis
Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer
Intrinsic Dimension Estimation Using Packing Numbers
Two Approaches to Optimal Annealing
Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations
Decoupled Kullback-Leibler Divergence Loss
Evaluating Attribution for Graph Neural Networks
LEADS: Learning Dynamical Systems that Generalize Across Environments
EMBERSim: A Large-Scale Databank for Boosting Similarity Search in Malware Analysis
Spartan: Differentiable Sparsity via Regularized Transportation
An Adaptive and Heterodyne Filtering Procedure for the Imaging of Moving Objects
Learning to Embed Distributions via Maximum Kernel Entropy
Confounding-Robust Policy Improvement
Causality Preserving Chaotic Transformation and Classification using Neurochaos Learning
Motivated Reinforcement Learning
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Fast structure learning with modular regularization
Feature Selection in Clustering Problems
FPNN: Field Probing Neural Networks for 3D Data
Well-tuned Simple Nets Excel on Tabular Datasets
Human-in-the-Loop Interpretability Prior
Collaborative Refining for Learning from Inaccurate Labels
Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier with Application to Real-Time Information Filtering on the Web
The Burer-Monteiro SDP method can fail even above the Barvinok-Pataki bound
Towards Multi-Domain Learning for Generalizable Video Anomaly Detection
Adjoint-aided inference of Gaussian process driven differential equations
Tractable Objectives for Robust Policy Optimization
Neural Analog Diffusion-Enhancement Layer and Spatio-Temporal Grouping in Early Vision
Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling
Look at What I'm Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos
Class-Disentanglement and Applications in Adversarial Detection and Defense
Learning Multiple Tasks using Manifold Regularization
Why think step by step? Reasoning emerges from the locality of experience
Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time
Program Synthesis Guided Reinforcement Learning for Partially Observed Environments
Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling
Object Classification from a Single Example Utilizing Class Relevance Metrics
Algorithms for Learning Markov Field Policies
Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity
Back to the Continuous Attractor
Contrastive Language-Image Pre-Training with Knowledge Graphs
Learning Cloth Dynamics: 3D+Texture Garment Reconstruction Benchmark
Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning
Direct value-approximation for factored MDPs
Neural Complexity Measures
Transfer Learning for Diffusion Models
Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, Vancouver, British Columbia, Canada
On the Power and Limitations of Random Features for Understanding Neural Networks
Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective
Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise
Learning with Average Top-k Loss
Privately Learning Mixtures of Axis-Aligned Gaussians
Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release
Scalable Demand-Aware Recommendation
Linear Convergence with Condition Number Independent Access of Full Gradients
Training DNNs with Hybrid Block Floating Point
Predicting Dynamic Difficulty
Understanding the Eluder Dimension
Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions
AGILE: A Novel Reinforcement Learning Framework of LLM Agents
Virtual Scanning: Unsupervised Non-line-of-sight Imaging from Irregularly Undersampled Transients
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
A Neural Oscillator Model of Auditory Selective Attention
Bayesian Warped Gaussian Processes
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction
Unified Inference for Variational Bayesian Linear Gaussian State-Space Models
Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn Owl
FINALLY: fast and universal speech enhancement with studio-like quality
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees
Analysis of Brain States from Multi-Region LFP Time-Series
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation
Robust Neural Contextual Bandit against Adversarial Corruptions
PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher
Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Continual World: A Robotic Benchmark For Continual Reinforcement Learning
Spiking Boltzmann Machines
Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
Priors for Diversity in Generative Latent Variable Models
Global Normalization for Streaming Speech Recognition in a Modular Framework
A Family of Robust Stochastic Operators for Reinforcement Learning
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring
Optimal Transport Model Distributional Robustness
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Black-Box Ripper: Copying black-box models using generative evolutionary algorithms
Compact Neural Volumetric Video Representations with Dynamic Codebooks
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation
Learning to Navigate Wikipedia by Taking Random Walks
Active Learning Helps Pretrained Models Learn the Intended Task
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Causal Fairness for Outcome Control
What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction
Segmental Neural Net Optimization for Continuous Speech Recognition
The Difficulty of Passive Learning in Deep Reinforcement Learning
RAGraph: A General Retrieval-Augmented Graph Learning Framework
Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model
Taming Fat-Tailed ("Heavier-Tailed" with Potentially Infinite Variance) Noise in Federated Learning
Open-Vocabulary Semantic Segmentation via Attribute Decomposition-Aggregation
Re-examination of the Role of Latent Variables in Sequence Modeling