yusuke1997/dblp-id-title huggingface dataset:
Symmetry Teleportation for Accelerated Optimization
Streaming Sparse Gaussian Process Approximations
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds
A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains
Revisiting Heterophily For Graph Neural Networks
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
An Analysis of Convex Relaxations for MAP Estimation
A Probabilistic Programming Approach To Probabilistic Data Analysis
Adaptive Linear Estimating Equations
Gradient Estimation Using Stochastic Computation Graphs
DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field
Provably Efficient Neural GTD for Off-Policy Learning
OW-VISCapTor: Abstractors for Open-World Video Instance Segmentation and Captioning
SE(3)-bi-equivariant Transformers for Point Cloud Assembly
Operational Fault Tolerance of CMAC Networks
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality
ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction
A Two-Stage Weighting Framework for Multi-Source Domain Adaptation
Learning Bayesian Networks with Thousands of Variables
Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems
ImageNet3D: Towards General-Purpose Object-Level 3D Understanding
Brant: Foundation Model for Intracranial Neural Signal
BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series
Estimating Analogical Similarity by Dot-Products of Holographic Reduced Representations
On Batch Teaching with Sample Complexity Bounded by VCD
Optimal Multiclass U-Calibration Error and Beyond
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting
LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
When to Update Your Model: Constrained Model-based Reinforcement Learning
Bayesian Learning of Sum-Product Networks
LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation
AudioMarkBench: Benchmarking Robustness of Audio Watermarking
HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
Wavelet Score-Based Generative Modeling
Dual Inhibitory Mechanisms for Definition of Receptive Field Characteristics in a Cat Striate Cortex
RobustBench: a standardized adversarial robustness benchmark
NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
Improved techniques for deterministic l2 robustness
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data
Active Negative Loss Functions for Learning with Noisy Labels
Boltzmann Machine Learning Using Mean Field Theory and Linear Response Correction
Learning to Order Things
Probabilistic low-rank matrix completion on finite alphabets
Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions
MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning
Efficient Discrepancy Testing for Learning with Distribution Shift
Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases
Exponential Quantum Communication Advantage in Distributed Inference and Learning
Kernel Projection Machine: a New Tool for Pattern Recognition
Spectral methods for neural characterization using generalized quadratic models
Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark
Saddle-to-Saddle Dynamics in Diagonal Linear Networks
Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design
Think Big, Teach Small: Do Language Models Distil Occam's Razor?
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification
Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches
Increasing Liquid State Machine Performance with Edge-of-Chaos Dynamics Organized by Astrocyte-modulated Plasticity
Learning Visual Attributes
Deep Neural Networks with Inexact Matching for Person Re-Identification
Discrete Flow Matching
Structure-Blind Signal Recovery
Learning Hierarchical Semantic Image Manipulation through Structured Representations
Selecting Weighting Factors in Logarithmic Opinion Pools
RRHF: Rank Responses to Align Language Models with Human Feedback
Bandit Quickest Changepoint Detection
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling
Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis
Fast Attention Requires Bounded Entries
Overcoming Brittleness in Pareto-Optimal Learning Augmented Algorithms
MERLOT: Multimodal Neural Script Knowledge Models
Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network
ATOMO: Communication-efficient Learning via Atomic Sparsification
Real-Time Selection Under General Constraints via Predictive Inference
GraphMorph: Tubular Structure Extraction by Morphing Predicted Graphs
K-level Reasoning for Zero-Shot Coordination in Hanabi
VisMin: Visual Minimal-Change Understanding
Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity
Limits of Transformer Language Models on Learning to Compose Algorithms
On some provably correct cases of variational inference for topic models
Tailoring Self-Attention for Graph via Rooted Subtrees
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms
Streaming Pointwise Mutual Information
A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs
CPM-Nets: Cross Partial Multi-View Networks
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
Leveraging Catastrophic Forgetting to Develop Safe Diffusion Models against Malicious Finetuning
Efficient Clustering for Stretched Mixtures: Landscape and Optimality
RecNorm: Simultaneous Normalisation and Classification Applied to Speech Recognition
Set2Graph: Learning Graphs From Sets
Causal Temporal Representation Learning with Nonstationary Sparse Transition
Invertible DenseNets with Concatenated LipSwish
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
Rate-coded Restricted Boltzmann Machines for Face Recognition
Universal Consistency of Multi-Class Support Vector Classification
Collaboration! Towards Robust Neural Methods for Routing Problems
Multiplicative Updating Rule for Blind Separation Derived from the Method of Scoring
SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems
Symplectic Nonlinear Component Analysis
Using a Translation-Invariant Neural Network to Diagnose Heart Arrhythmia
Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features
Spatial Organization of Neural Networks: A Probabilistic Modeling Approach
Efficient Online Linear Optimization with Approximation Algorithms
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives
Neural Networks Weights Quantization: Target None-retraining Ternary (TNT)
(Almost) Free Incentivized Exploration from Decentralized Learning Agents
Classifying Hand Gestures with a View-Based Distributed Representation
Transcendence: Generative Models Can Outperform The Experts That Train Them
Change-point Detection for Sparse and Dense Functional Data in General Dimensions
Support Vector Method for Function Approximation, Regression Estimation and Signal Processing
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes
Back Propagation Implementation
Learning Manifold Implicitly via Explicit Heat-Kernel Learning
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection
A Hybrid Radial Basis Function Neurocomputer and Its Applications
Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making
Sequential Experimental Design for Transductive Linear Bandits
On the Pseudo-Dimension of Nearly Optimal Auctions
Learning General World Models in a Handful of Reward-Free Deployments
Learning with Compressible Priors
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
Compositional De-Attention Networks
CropHarvest: A global dataset for crop-type classification
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects
Can multi-label classification networks know what they don't know?
CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models
On the interplay between data structure and loss function in classification problems
Inference in Multilayer Networks via Large Deviation Bounds
Evidence for a Forward Dynamics Model in Human Adaptive Motor Control
Sphere Embedding: An Application to Part-of-Speech Induction
Continuous-time Models for Stochastic Optimization Algorithms
Mid-level Visual Element Discovery as Discriminative Mode Seeking
SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement
Hamming Distance Metric Learning
Fairness in Ranking under Uncertainty
Bayesian models of human action understanding
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
Sequential Subset Matching for Dataset Distillation
DC-BENCH: Dataset Condensation Benchmark
Neural Code Comprehension: A Learnable Representation of Code Semantics
Agreement-Based Learning
Chemosensory Processing in a Spiking Model of the Olfactory Bulb: Chemotopic Convergence and Center Surround Inhibition
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning
Inherently Explainable Reinforcement Learning in Natural Language
Visual Navigation in a Robot Using Zig-Zag Behavior
Learning Adaptive Value of Information for Structured Prediction
Stochastic Convex Optimization with Multiple Objectives
Developing Topography and Ocular Dominance Using Two aVLSI Vision Sensors and a Neurotrophic Model of Plasticity
Predictive Representations of State
Learning About Multiple Objects in Images: Factorial Learning without Factorial Search
Learning Spatio-Temporal Planning from a Dynamic Programming Teacher: Feed-Forward Neurocontrol for Moving Obstacle Avoidance
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator
Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment
Structure Learning in Human Causal Induction
On the consistent estimation of optimal Receiver Operating Characteristic (ROC) curve
Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD
Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach
Faster proximal algorithms for matrix optimization using Jacobi-based eigenvalue methods
Practical Adversarial Multivalid Conformal Prediction
Tackling Uncertain Correspondences for Multi-Modal Entity Alignment
Learning Motion Style Synthesis from Perceptual Observations
Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation
Reward Augmented Maximum Likelihood for Neural Structured Prediction
Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning
Provable benefits of score matching
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
NeuMiss networks: differentiable programming for supervised learning with missing values
A Model of the Neural Basis of the Rat's Sense of Direction
A Neural-Network Solution to the Concentrator Assignment Problem
Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection
Pre-activation Distributions Expose Backdoor Neurons
Bayesian Optimization of Risk Measures
A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction
Explicit Regularisation in Gaussian Noise Injections
Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters
Spherization Layer: Representation Using Only Angles
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Edges are the Independent Components of Natural Scenes
A probability contrastive learning framework for 3D molecular representation learning
Dependent nonparametric trees for dynamic hierarchical clustering
What is my quantum computer good for? Quantum capability learning with physics-aware neural networks
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces
RTify: Aligning Deep Neural Networks with Human Behavioral Decisions
Testing a Bayesian Measure of Representativeness Using a Large Image Database
Sparse High Rank Adapters
Django: Detecting Trojans in Object Detection Models via Gaussian Focus Calibration
Multi-Scale Representation Learning on Proteins
Differentiable MPC for End-to-end Planning and Control
Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
Approximation-Aware Bayesian Optimization
Constrained Human-AI Cooperation: An Inclusive Embodied Social Intelligence Challenge
Variational Multi-Task Learning with Gumbel-Softmax Priors
Regret Analysis for Continuous Dueling Bandit
SURGE: Surface Regularized Geometry Estimation from a Single Image
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual
WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise
Receptive Fields without Spike-Triggering
Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm
HYDRA: Pruning Adversarially Robust Neural Networks
Action-guided 3D Human Motion Prediction
Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration
Balancing Between Bagging and Bumping
Efficient Graph Generation with Graph Recurrent Attention Networks
SmoothHess: ReLU Network Feature Interactions via Stein's Lemma
Error Bounds for Transductive Learning via Compression and Clustering
Non-Rigid Shape Registration via Deep Functional Maps Prior
Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesis
Optimal Learning for Multi-pass Stochastic Gradient Methods
GAN Memory with No Forgetting
Smooth Flipping Probability for Differential Private Sign Random Projection Methods
Mixed vine copulas as joint models of spike counts and local field potentials
Laplace Redux - Effortless Bayesian Deep Learning
De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
A Scalable Deterministic Global Optimization Algorithm for Training Optimal Decision Tree
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants
The Pitfalls of Regularization in Off-Policy TD Learning
Fast and Memory Optimal Low-Rank Matrix Approximation
NanoBaseLib: A Multi-Task Benchmark Dataset for Nanopore Sequencing
Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials
Exploring the Whole Rashomon Set of Sparse Decision Trees
Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks
Coin Betting and Parameter-Free Online Learning
Accuracy and Interpretability Trade-Offs in Machine Learning Applied to Safer Gambling
Learning from the Wisdom of Crowds by Minimax Entropy
The Fidelity of Local Ordinal Encoding
On Success and Simplicity: A Second Look at Transferable Targeted Attacks
E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding
Recurrent Transformer Networks for Semantic Correspondence
Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation
Understanding Batch Normalization
Pay attention to your loss : understanding misconceptions about Lipschitz neural networks
Amplifying and Linearizing Apical Synaptic Inputs to Cortical Pyramidal Cells
Bidirectional Retrieval from Associative Memory
Robot Learning: Exploration and Continuous Domains
Nested sampling for Potts models
Discontinuous Recall Transitions Induced by Competition Between Short- and Long-Range Interactions in Recurrent Networks
Online Classification with Predictions
Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface
Online Discovery and Learning of Predictive State Representations
Scalable Variational Inference for Dynamical Systems
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving
ICNet: Intra-saliency Correlation Network for Co-Saliency Detection
Benchmarking Bias Mitigation Algorithms in Representation Learning through Fairness Metrics
On Multiplicative Multitask Feature Learning
Online List Labeling with Predictions
Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
Playing Minecraft with Behavioural Cloning
$\theta$-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding
On the Concentration of Expectation and Approximate Inference in Layered Networks
Residual Q-Learning: Offline and Online Policy Customization without Value
Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts
Cross-Domain Transferability of Adversarial Perturbations
Generalization Bounds for Neural Networks via Approximate Description Length
Directed Spectrum Measures Improve Latent Network Models Of Neural Populations
A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning
On Inductive Biases for Heterogeneous Treatment Effect Estimation
Less is More: Nyström Computational Regularization
Reformulating Zero-shot Action Recognition for Multi-label Actions
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance
Neural Network Models for Optimization Problems
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification
Ensemble Distillation for Robust Model Fusion in Federated Learning
Simple, Scalable and Effective Clustering via One-Dimensional Projections
Segmenting Watermarked Texts From Language Models
Crossmodal Language Grounding, Learning, and Teaching
Gone Fishing: Neural Active Learning with Fisher Embeddings
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world
Most Activation Functions Can Win the Lottery Without Excessive Depth
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation
A Spectral View of Adversarially Robust Features
Probabilistic Forecasting: A Level-Set Approach
Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
A Universal Primal-Dual Convex Optimization Framework
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Evidence-Specific Structures for Rich Tractable CRFs
Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning
Geometry of Early Stopping in Linear Networks
Bounded Invariance and the Formation of Place Fields.
Joint processing of linguistic properties in brains and language models
New Rules for Domain Independent Lifted MAP Inference
Revisiting Non-Parametric Matching Cost Volumes for Robust and Generalizable Stereo Matching
Learning Stochastic Feedforward Neural Networks
Multi-Armed Bandits with Bounded Arm-Memory: Near-Optimal Guarantees for Best-Arm Identification and Regret Minimization
Task-level Differentially Private Meta Learning
Learning Debiased and Disentangled Representations for Semantic Segmentation
Learning Energy-Based Prior Model with Diffusion-Amortized MCMC
Shield Decentralization for Safe Multi-Agent Reinforcement Learning
Distributionally Robust Local Non-parametric Conditional Estimation
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
A Simple and Fast Neural Network Approach to Stereovision
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products
Approximating Sparse PCA from Incomplete Data
Functional Indirection Neural Estimator for Better Out-of-distribution Generalization
Dancing to Music
Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization
YouDream: Generating Anatomically Controllable Consistent Text-to-3D Animals
Log-Polar Space Convolution Layers
On the choice of Perception Loss Function for Learned Video Compression
Heterogeneous multitask learning with joint sparsity constraints
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification
Online Planning with Lookahead Policies
Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering
Dynamic Modulation of Neurons and Networks
Understanding Adaptive, Multiscale Temporal Integration In Deep Speech Recognition Systems
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality
Improving Sparse Vector Technique with Renyi Differential Privacy
SQ Lower Bounds for Learning Single Neurons with Massart Noise
Diffusion Models are Certifiably Robust Classifiers
Fine-Grained Analysis of Stability and Generalization for Modern Meta Learning Algorithms
Non-adversarial training of Neural SDEs with signature kernel scores
Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons
Graph Neural Networks with Adaptive Residual
Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark
Multiple Choice Learning: Learning to Produce Multiple Structured Outputs
PAC Prediction Sets for Meta-Learning
Ultrafast classical phylogenetic method beats large protein language models on variant effect prediction
Upping the Game: How 2D U-Net Skip Connections Flip 3D Segmentation
Learning in Compositional Hierarchies: Inducing the Structure of Objects from Data
Efficient Online Clustering with Moving Costs
Spike timing and the coding of naturalistic sounds in a central auditory area of songbirds
On the Local Hessian in Back-propagation
On provable privacy vulnerabilities of graph representations
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
An Embedding Framework for Consistent Polyhedral Surrogates
Illumination and View Position in 3D Visual Recognition
Reparameterization Gradient for Non-differentiable Models
On the Error Resistance of Hinge-Loss Minimization
Misspecified Phase Retrieval with Generative Priors
Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation
Finite-Time Analysis of Single-Timescale Actor-Critic
Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent
Adaptive Q-Aid for Conditional Supervised Learning in Offline Reinforcement Learning
Subject independent EEG-based BCI decoding
Decoding Cursive Scripts
Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex
Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models
ID-to-3D: Expressive ID-guided 3D Heads via Score Distillation Sampling