MAC Advice for Facility Location Mechanism Design

Learning-Augmented Algorithms with Explicit Predictors

To Trust or Not to Trust: Assignment Mechanisms with Predictions in the Private Graph Model

Energy-Efficient Scheduling with Predictions

Max-Cut with ε-Accurate Predictions

Learning-Based Algorithms for Graph Searching Problems

Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model

Chasing Convex Functions with Long-term Constraints

Learning-Augmented Skip Lists

Robust Learning-Augmented Dictionaries

Parsimonious Learning-Augmented Approximations for Dense Instances of NP-hard Problems

Online Bin Covering with Frequency Predictions

Randomized learning-augmented auctions with revenue guarantees

Credence: Augmenting Datacenter Switch Buffer Sharing with ML Predictions

Competitive Search in the Line and the Star with Predictions

Online Covering with Multiple Experts

Connectivity Oracles for Predictable Vertex Failures

Improved Frequency Estimation Algorithms with and without Predictions

On Optimal Consistency-Robustness Trade-Off for Learning-Augmented Multi-Option Ski Rental

Online Graph Coloring with Predictions

Learning-Augmented Dynamic Submodular Maximization

Sorting with Predictions

Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms

Online Algorithms with Uncertainty-Quantified Predictions

Online Mechanism Design with Predictions

Competitive Auctions with Imperfect Predictions

On the Complexity of Algorithms with Predictions for Dynamic Graph Problems

Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions

On Dynamic Graph Algorithms with Predictions

The Predicted-Deletion Dynamic Model: Taking Advantage of ML Predictions, for Free

LearnedSort as a learning-augmented SampleSort: Analysis and Parallelization

Optimal Metric Distortion with Predictions

Online Resource Allocation with Convex-set Machine-Learned Advice

Learning-Augmented Decentralized Online Convex Optimization in Networks

The Secretary Problem with Predictions

Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case

Active causal structure learning with advice

A General Framework for Learning-Augmented Online Allocation

Online Dynamic Acknowledgement with Learned Predictions

Time Fairness in Online Knapsack Problems

Online List Labeling with Predictions

The Nonstationary Newsvendor with (and without) Predictions

Learning-Augmented Online Packet Scheduling with Deadlines

Learning-Augmented Online TSP on Rings, Trees, Flowers and (almost) Everywhere Else

Learned Interpolation for Better Streaming Quantile Approximation with Worst Case Guarantees

Mixing predictions for online metric algorithms

Online Time-Windows TSP with Predictions

Predictive Flows for Faster Ford-Fulkerson

Bicriteria Multidimensional Mechanism Design with Side Information

Online Interval Scheduling with Predictions

Online Minimum Spanning Trees with Weight Predictions

Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis

Speed-Oblivious Online Scheduling: Knowing (Precise) Speeds is not Necessary

Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L-Convex Function Minimization

Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints

Renyi-Ulam Games and Online Computation with Imperfect Advice

The Safe and Effective Use of Low-Assurance Predictions in Safety-Critical Systems

Discrete-Smoothness in Online Algorithms with Predictions

Advice Querying under Budget Constraint for Online Algorithms

Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems

Online Algorithms with Costly Predictions

Online State Exploration: Competitive Worst Case and Learning-Augmented Algorithms

Speeding Up Bellman Ford via Minimum Violation Permutations

Applied Online Algorithms with Heterogeneous Predictors

KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals

Graph Searching with Predictions

Scheduling with Predictions

Mechanism Design With Predictions for Obnoxious Facility Location

On the Power of Learning-Augmented BSTs

Online Search with Predictions: Pareto-optimal Algorithm and its Applications in Energy Markets

Improved Learning-augmented Algorithms for k-means and k-medians Clustering

Algorithms with Prediction Portfolios

Private Algorithms with Private Predictions

Paging with Succinct Predictions

Proportionally Fair Online Allocation of Public Goods with Predictions

Canadian Traveller Problem with Predictions

Learning-Augmented Algorithms for Online Linear and Semidefinite Programming

Strategyproof Scheduling with Predictions

Learning-Augmented Maximum Flow

Online Prediction in Sub-linear Space

Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty

Online TSP with Predictions

Learning-Augmented Binary Search Trees

Chasing Convex Bodies and Functions with Black-Box Advice

Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model

Learning-Augmented Algorithms for Online TSP on the Line

On Preemption and Learning in Stochastic Scheduling

A Universal Error Measure for Input Predictions Applied to Online Graph Problems

Mechanism Design with Predictions

Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions

A Regression Approach to Learning-Augmented Online Algorithms

Customizing ML Predictions For Online Algorithms

Improved Price of Anarchy via Predictions

Online Algorithms with Multiple Predictions

Scheduling with Speed Predictions

Faster Fundamental Graph Algorithms via Learned Predictions

Learning-Augmented k-means Clustering

Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location

Triangle and Four Cycle Counting with Predictions in Graph Streams

Online Unit Profit Knapsack with Untrusted Predictions

Permutation Predictions for Non-Clairvoyant Scheduling

Single-Leg Revenue Management with Advice

Learning Predictions for Algorithms with Predictions

Parsimonious Learning-Augmented Caching

Lazy Lagrangians with Predictions for Online Learning

Distortion-Oblivious Algorithms for Scheduling on Multiple Machines

Scheduling with Untrusted Predictions

Machine Learning Advised Ski Rental Problem with a Discount

Robust Load Balancing with Machine Learned Advice

Learning-augmented algorithms for online subset sum

Brief Announcement: Towards a More Robust Algorithm for Flow Time Scheduling with Predictions

Uniform Machine Scheduling with Predictions

Real-Time Scheduling with Predictions

Online Graph Algorithms with Predictions

Using Machine Learning Predictions to Speed-up Dijkstra's Shortest Path Algorithm

Robustification of Online Graph Exploration Methods

Learning-Augmented Algorithms for Online Steiner Tree

A Novel Prediction Setup for Online Speed-Scaling

Competitive Sequencing with Noisy Advice

Logarithmic Regret from Sublinear Hints

Learning-Augmented Dynamic Power Management with Multiple States via New Ski-Rental Bounds

Can Q-Learning be Improved with Advice?

Online Facility Location with Predictions

Online Primal-Dual Algorithms with Predictions for Packing Problems

Uniform Bounds for Scheduling with Job Size Estimates

Distortion-Oblivious Algorithms for Minimizing Flow Time

Pareto-optimal learning-augmented algorithms for online conversion problems

Learning to Hash Robustly, Guaranteed

Faster Matchings via Learned Duals

Learning Augmented Online Facility Location

Optimal Stopping Methodology for the Secretary Problem with Random Queries

Robust Learning-Augmented Caching: An Experimental Study

Robustness and Consistency in Linear Quadratic Control with Untrusted Predictions

Learning-based support estimation in sublinear time

Using Predicted Weights for Ad Delivery

Flow Time Scheduling with Uncertain Processing Time

Double Coverage with Machine-Learned Advice

Online Bin Packing with Predictions

Online Bipartite Matching with Predicted Degrees

Online Facility Location with Multiple Advice

A learned approach to design compressed rank/select data structures

Learning Online Algorithms with Distributional Advice

Putting the \"Learning\" into Learning-Augmented Algorithms for Frequency Estimation

On the performance of learned data structures

Repetition- and Linearity-Aware Rank/Select Dictionaries

Non-Clairvoyant Scheduling with Predictions

Online Knapsack with Frequency Predictions

Online peak-aware energy scheduling with untrusted advice

Online Unrelated Machine Load Balancing with Predictions Revisited

A New Approach to Capacity Scaling Augmented With Unreliable Machine Learning Predictions

Prediction Augmented Segment Routing

Data-driven Competitive Algorithms for Online Knapsack and Set Cover

Contract scheduling with predictions

Learnable and Instance-Robust Predictions for Online Matching, Flows and Load Balancing

Learning-Augmented Weighted Paging

Online Paging with a Vanishing Regret

Secretaries with Advice

Generalized Sorting with Predictions

Learning Augmented Energy Minimization via Speed Scaling

The Primal-Dual method for Learning Augmented Algorithms

Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms

Online Search With a Hint

Online Nash Social Welfare Maximization with Predictions

Queues with Small Advice

Online Algorithms for Weighted Paging with Predictions

Algorithms with Predictions

Online Page Migration with ML Advice

Secretary and Online Matching Problems with Machine Learned Advice

Better and simpler learning-augmented online caching

Online metric algorithms with untrusted predictions

Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice

Improving Online Rent-or-Buy Algorithms with Sequential Decision Making and ML Predictions

Untrusted Predictions Improve Trustable Query Policies

The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds

Learning-augmented data stream algorithms

Online scheduling via learned weights

Near-optimal bounds for online caching with machine learned advice

(Learned) Frequency Estimation Algorithms under Zipfian Distribution

The Supermarket Model with Known and Predicted Service Times

Online Computation with Untrusted Advice

Scheduling with Predictions and the Price of Misprediction

A model for learned bloom filters and optimizing by sandwiching

Learned data structures

Online algorithms for rent-or-buy with expert advice

Learning-Based Frequency Estimation Algorithms

Learning-Based Low-Rank Approximations

Competitive Caching with Machine Learned Advice

Improving online algorithms via ML predictions

The Case for Learned Index Structures