Study validates Twitter search protocol for health and disease events.
problem Validating search protocols for health-related tweets on Twitter.
method Extracted and analyzed health and disease tweets using predefined keywords, trained CART algorithms for predictions.
result Validation showed good accuracy (AUC > 0.8) in detecting relevant health and disease tweets.
SANNS secures k-NNS queries and results without revealing them.
problem Securely searching for nearest neighbors without exposing sensitive data.
method Optimized linear scan and clustering-based algorithm with cryptographic primitives.
result SANNS achieves up to 31x faster response times and scales to 10 million entries.
NAS evaluation is hard due to lack of standard protocols.
problem Difficulty in comparing NAS methods due to varying search spaces and evaluation protocols.
method Benchmarked 8 NAS methods on 5 datasets, proposing a relative improvement metric over random architectures.
result Many NAS techniques struggle to significantly outperform a randomly generated architecture.
LLM agents discover cryptocurrency factors under reproducible constraints.
problem Flexibility of LLM agents in empirical discovery leads to uncontrolled search.
method Sequential hypothesis search with fixed data splits and portfolio tests.
result Ridge-combined portfolio achieves 44.55% annualized return in out-of-sample period.
Simple embedding models outperform complex ones in knowledge base completion.
problem Improving the accuracy of knowledge base completion using embedding models.
method Evaluation of embedding models for knowledge base completion using different protocols and a rule-based baseline.
result Current embedding models perform poorly in knowledge base completion compared to a simple rule-based approach.
New benchmark protocol evaluates neural network optimizers for efficiency and data shift sensitivity.
problem Benchmarking neural network optimizers with hyperparameter complexity and data shift sensitivity.
method Proposed a new evaluation protocol combining end-to-end and data-addition training efficiency, using bandit hyperparameter tuning and human study validation.
result No clear winner across all tasks, highlighting the complexity of optimizer performance.
Researchers develop multi-agent systems for quadcopters to collaborate in missions.
problem Enable multiple quadcopters to work together in remote sensing tasks.
method Agent dynamics, network topologies, collective behaviors, agreement protocol, equations of motion for quadcopters.
result Multi-agent systems can successfully collaborate in remote sensing missions.
There are recent cryptographic protocols that are based on Multiple Simultaneous Conjugacy Problems in braid groups. We improve an algorithm, due to Sang Jin Lee and Eonkyung Lee, to solve these problems, by applying a method developed by the author and Nuno Franco, originally intended to solve the Conjugacy Search Pro…
Elastic Gossip distributes neural network training using gossip-like protocols.
problem Distributing neural network training across heterogeneous environments.
method Pairwise-communication using Gossip-like protocols, building on Elastic Averaging SGD.
result Elastic Gossip performs better than Gossiping SGD in experiments, but hyper-parameter search may yield better configurations.
SIREN protocol corrects optimistic winner's scores in LLM evaluation.
problem Optimistic winner's scores in LLM evaluation due to adaptive benchmarking.
method SIREN protocol that freezes post-search shortlist, separates selection and evaluation, and uses bootstrap for uncertainty quantification.
result SIREN provides valid confidence intervals for procedure-performance curves and deployment conclusions.
Automates supervised learning pipeline design with matrix and tensor factorization.
problem Designing effective supervised learning pipelines with many choices.
method Uses matrix and tensor factorization to model pipeline search space and develops greedy experiment design protocols.
result Demonstrates the effectiveness of the approach on real-world classification problems.
TabNAS improves neural architecture search for tabular datasets by rejecting suboptimal architectures.
problem Finding optimal neural architectures for tabular datasets with resource constraints.
method Develops a reinforcement learning controller motivated by rejection sampling to handle resource constraints.
result TabNAS finds better models that obey resource constraints compared to previous methods.
Method retrieves similar fashion items from images and text, enabling style refinement.
problem Lack of intuitive, interactive refinement in search engines for fashion items.
method Joint visual-textual embedding training, Mini-Batch Match Retrieval, attribute extraction.
result Improved performance in multimodal style search, demonstrated through benchmark.
Machine learning identifies hidden spin nematics in magnetic configurations.
problem Challenging identification of unconventional magnetic states.
method Interpretable machine learning protocol for detecting nematic order.
result Extracted analytical forms of nematic order parameters up to rank 6.
The paper studies how search and distillation improve reasoning in large language models.
problem Improving reasoning capabilities of large language models.
method Viewing chain-of-thought generation as a metastable Markov process, proving benefits of search and distillation.
result Search protocol rewards sparse edges, reducing the expected number of steps to reach different clusters.
Optimized reverse quantum annealing speeds up portfolio optimization.
problem Optimizing portfolios using quantum and classical methods.
method Hybrid quantum-classical approach, including reverse quantum annealing.
result Optimized reverse quantum annealing is 100 times faster than forward quantum annealing.
Proposes a heuristic to dynamically control exploration vs exploitation in Bayesian optimization.
problem The trade-off between exploration and exploitation in Bayesian optimization methods.
method Contextual Improvement heuristic to dynamically control the trade-off.
result Improves the speed and robustness of discovering optimal solutions.
This paper explores how interactive protocols enhance local differential privacy.
problem The power of interactive protocols in local differential privacy.
method Classification of locally private protocols by compositionality and transformation of fully interactive protocols into sequentially interactive ones.
result Fully interactive protocols can solve problems that sequentially interactive protocols cannot without a significant increase in sample complexity.
Maker Protocol manages Dai stable coin on Ethereum blockchain.
problem Managing decentralized finance applications on blockchain.
method Analyzes Maker Protocol's components and governance.
result Maker Protocol is a significant decentralized finance application.
Compound Finance optimizes risk metrics for V3 protocol using Chainrisk simulations.
problem Optimizing systemic risks in Compound V3 protocol.
method Millions of Chainrisk simulations to evaluate VaR and LaR, providing parameter adjustments.
result Optimization framework enhances protocol stability.
This paper examines interest rates and market efficiency in DeFi loanable funds protocols.
problem Equilibrium of supply and demand for loanable funds in DeFi protocols.
method Review of interest rate mechanisms in Compound, Aave, and dYdX; empirical analysis of market efficiency and inter-connectedness.
result Interest rate rules in DeFi protocols do not always equilibrate supply and demand.
NAS improves blockchain-based cryptocurrency predictions.
problem Efficiently designing and optimizing neural networks for cryptocurrency prediction.
method Customized Neural Architecture Search (NAS) with network morphism and Bayesian optimization.
result NAS algorithms can achieve results comparable to manually designed models.
New federated learning protocols resist Byzantine failures and offer privacy guarantees.
problem Resisting Byzantine failures in federated learning.
method Proposes robust federated learning protocols with optimal statistical rates and privacy guarantees.
result Achieves nearly optimal statistical rates and tight rate in terms of all parameters for strongly convex losses.
The paper analyzes how mutable blockchain protocols affect miner behavior and strategic stability.
problem The mutability of blockchain protocols undermines long-term planning and cooperative equilibria.
method Integrates Austrian capital theory with repeated game theory to examine miner behavior under different institutional conditions.
result Effective time preference increases when protocol rules are mutable, leading to political rent-seeking and undermining strategic coherence.
Protocol minimizes disclosure in classification tasks.
problem Ensuring minimal disclosure in classification protocols.
method Developed a protocol for multi-party classification that minimizes non-responsive document disclosure.
result Guarantees minimal disclosure of non-responsive documents.
This study measures liquidity risks in Aave, a blockchain lending protocol.
problem Liquidity risks in lending protocols, especially in Aave.
method Measurements of liquidity risks using Aave as a case study, focusing on available liquidity and market concentration.
result Liquidity risks in Aave are volatile and affect the protocol negatively, especially for repeat borrowers.
Paper presents a risk management framework for blockchain protocols.
problem Blockchain protocol risks affecting DLT and digital assets.
method Developed a comprehensive risk management framework using traditional taxonomy.
result Structured approach to identify, measure, monitor and report blockchain protocol risks.
Study analyzes risk management in Aave and Compound lending protocols, finding v3 better than v2.
problem Risk management in decentralized lending protocols.
method Cross-version and cross-chain analysis using fixed effects model.
result v3 protocols have better risk management, with stronger impact on L2 blockchains.
Automated medical protocol uses neural networks and decision trees.
problem Improving healthcare delivery through automated decision-making.
method Hybrid model combining neural networks and decision trees.
result Effective early decisions for patient care.
The paper gives bounds for how long it takes for gossip protocols to spread information in networks.
problem Understanding the diffusion time in asynchronous gossip protocols.
method Provides non-asymptotic bounds for the number of messages needed for consensus in asynchronous gossip protocols.
result Explicit formula and approximation for the number of messages needed for consensus in different types of graphs.
Paper uses weakly-supervised clustering to automatically create network protocol abstractions.
problem Manual definition of abstraction by domain experts is time-consuming.
method Weakly supervised clustering algorithm for automatic abstraction.
result The method successfully matches the reference abstraction with minimal labeled examples.
Paper explores how to design federated learning protocols that benefit all participants while maintaining privacy.
problem Privacy concerns undermine the accuracy benefits of federated learning in privacy-sensitive domains.
method The paper provides conditions for mutually beneficial federated learning protocols and designs protocols that maximize total utility and accuracy.
result The paper demonstrates that federated learning can be designed to be mutually beneficial, striking a balance between privacy and model accuracy.
Improved privacy-preserving summation protocol with fewer messages.
problem Achieving efficient differential privacy in multi-party summation.
method Combining secure shuffling with Laplace mechanism in the shuffle model.
result Protocol with O(1/ε) error and O(log(n/δ)) messages per party. Quantum reinforcement learning protocols implemented in superconducting circuits.
problem Improving quantum devices through learning processes.
method Implementation of quantum reinforcement learning protocols using superconducting circuits.
result Feasibility analysis of quantum reinforcement learning protocols in superconducting circuits.
FEET protocol evaluates foundation models across three scenarios.
problem Lack of standardized evaluation protocols for foundation models.
method Structured evaluation protocol across three use cases: frozen, few-shot, and fine-tuned embeddings.
result Demonstrates comprehensive assessment of foundation models' effectiveness.
A scalable protocol for federated averaging with privacy and correctness guarantees.
problem Privacy and correctness in federated learning from multiple parties.
method Scalable protocol using correlated and independent Gaussian noise, analyzed for differential privacy and graph topology.
result Nearly matches trusted curator model's utility with minimal communication.
The paper examines how optimizer comparisons in deep learning are influenced by hyperparameter tuning.
problem The sensitivity of optimizer comparisons to hyperparameter tuning protocols.
method Empirical comparisons of optimizers with and without varying hyperparameter search spaces.
result Inclusion relationships between optimizers matter in practice and can contradict recent empirical comparisons.
Survey of yield farming protocols in DeFi.
problem Understanding and evaluating yield farming mechanisms in DeFi.
method Analyzed smart contracts, performed simulations, reviewed literature.
result Characterized major yield aggregators and identified risks.
New protocol makes federated learning more scalable and private.
problem Securely aggregate data from distributed, private datasets.
method Proposes a new protocol for aggregation in the shuffled model that is more efficient in terms of communication and error.
result Achieves differential privacy guarantees with polylogarithmic scaling in the number of users.
Paper proposes communication protocols for RL in swarm robotics.
problem Learning decentralized control policies in multi-robot swarms with limited sensing and communication.
method Simple communication protocols based on histograms and task-specific information.
result Deep RL can find effective decentralized control policies using proposed communication protocols.
A new cryptocurrency issuance protocol using proof-of-work without mining electricity.
problem Creating digital currencies without relying on electricity.
method Alternative asset utilization for cryptocurrency creation.
result Supports digital currencies in a proof-of-work manner without mining electricity.
This study aims to improve communication between fragmented blockchain systems in finance.
problem Inefficient and insecure communication in fragmented blockchain systems.
method Analysis of cross-chain interoperability protocols and their properties.
result Comparison and evaluation of cross-chain interoperability protocols.
Proposes clustering as a new evaluation method for clinical knowledge embedding.
problem Traditional Link Prediction evaluation protocol loses information and harms model accuracy.
method Proposes Clustering Evaluation Protocol as an alternative.
result Experimental results show the proposed protocol can potentially replace Link Prediction.
Paper designs efficient data compression and MAC protocol for smartgrids.
problem Efficiently compress and transmit data from smartgrids with renewable energy.
method Uses compressed sensing (CS) for data compression and adapts 802.15.4 MAC protocol for reliable transmission.
result Minimizes reporting delay and ensures reliable data reconstruction.
Study analyzes financial intermediation costs in decentralized lending protocols.
problem Understanding the cost of financial intermediation in decentralized lending protocols.
method Analysis of publicly available data on rates, supply, borrow activity, and accounts.
result Ex-post margins are 1% and lower for stablecoin markets.
New protocol reduces communication costs for heterogeneous bandits over complex networks.
problem Minimizing group regret in a multi-agent, heterogeneous bandit setting over complex networks.
method Flooding with Absorption (FwA) protocol for heterogeneous bandits over complex networks.
result FwA protocol significantly reduces communication costs compared to flooding while maintaining similar regret performance.
The paper analyzes risks and revenue dynamics of a liquid restaking protocol in decentralized finance.
problem Interconnected risks and revenue dynamics of a liquid restaking protocol in decentralized finance.
method Empirical analysis using OLS regression, Granger-causality, and random forest feature importance tests.
result Revenue is primarily driven by value locked in the ecosystem, yield of liquid restaking token, and multi-blockchain expansion.
The study analyzes how cross-chain interoperability affects decentralized lending protocols' performance.
problem Understudied cross-chain elements in DeFi lending risk management.
method Panel regression fixed effects and OLS models applied to empirical analysis.
result Cross-chain activity impacts protocol performance, with bridge volume being a critical driver.